Relevant bibliographies by topics / Images PET

Academic literature on the topic 'Images PET'

Author: Grafiati
Published: 7 July 2024
Last updated: 7 July 2024

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Journal articles on the topic "Images PET":

1

Muraglia, Lorenzo, Francesco Mattana, Laura Lavinia Travaini, Gennaro Musi, Emilio Bertani, Giuseppe Renne, Eleonora Pisa, et al. "First Live-Experience Session with PET/CT Specimen Imager: A Pilot Analysis in Prostate Cancer and Neuroendocrine Tumor." Biomedicines 11, no. 2 (February 20, 2023): 645. http://dx.doi.org/10.3390/biomedicines11020645.

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Objective: to evaluate the feasibility of the intra-operative application of a specimen PET/CT imager in a clinical setting. Materials and methods: this is a pilot analysis performed in three patients who received an intra-operative administration of 68Ga-PSMA-11 (n = 2) and 68Ga-DOTA-TOC (n = 1), respectively. Patients were administrated with PET radiopharmaceuticals to perform radio-guided surgery with a beta-probe detector during radical prostatectomy for prostate cancer (PCa) and salvage lymphadenectomy for recurrent neuroendocrine tumor (NET) of the ileum, respectively. All procedures have been performed within two ongoing clinical trials in our Institute (NCT05596851 and NCT05448157). Pathologic assessment with immunohistochemistry (PSMA-staining and SSA immunoreactivity) was considered as standard of truth. Specimen images were compared with baseline PET/CT images and histopathological analysis. Results: Patients received 1 MBq/Kg of 68Ga-PSMA-11 (PCa) or 1.2 MBq/Kg of 68Ga-DOTA-TOC (NET) prior to surgery. Specimens were collected, positioned in the dedicated specimen container, and scanned to obtain high-resolution PET/CT images. In all cases, a perfect match was observed between the findings detected by the specimen imager and histopathology. Overall, the PET spatial resolution was sensibly higher for the specimen images compared to the baseline whole-body PET/CT images. Furthermore, the use of the PET/CT specimen imager did not significantly interfere with any procedures, and the overall length of the surgery was not affected using the PET/CT specimen imager. Finally, the radiation exposure of the operating theater staff was lower than 40 µSv per procedure (range 26–40 μSv). Conclusions: the image acquisition of specimens obtained by patients who received intra-surgery injections of 68Ga-PSMA-11 and 68Ga-DOTA-TOC was feasible and reliable also in a live-experience session and has been easily adapted to surgery daily practice. The high sensitivity, together with the evaluation of intra-lesion tumor heterogeneity, were the most relevant results since the data derived from specimen PET/CT imaging matched perfectly with the histopathological analysis.
2

Gershon, Nahum D. "Visualizing 3D PET Images." IEEE Computer Graphics and Applications 11, no. 5 (September 1991): 11–13. http://dx.doi.org/10.1109/mcg.1991.10040.

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Jiang, Changhui, Xu Zhang, Na Zhang, Qiyang Zhang, Chao Zhou, Jianmin Yuan, Qiang He, et al. "Synthesizing PET/MR (T1-weighted) images from non-attenuation-corrected PET images." Physics in Medicine & Biology 66, no. 13 (June 24, 2021): 135006. http://dx.doi.org/10.1088/1361-6560/ac08b2.

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4

Pietrzyk, U., C. Knoess, S. Vollmar, K. Wienhard, L. Kracht, A. Bockisch, S. Maderwald, H. Kühl, M. Fitzek, and T. Beyer. "Multi-modality imaging of uveal melanomas using combined PET/CT, high-resolution PET and MR imaging." Nuklearmedizin 47, no. 02 (2008): 73–79. http://dx.doi.org/10.3413/nukmed-0125.

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SummaryWe investigated the efficacy of combined FDG-PET/CT imaging for the diagnosis of small-size uveal melanomas and the feasibility of combining separate, high-resolution (HR) FDG-PET with MRI for its improved localization and detection. Patients, methods: 3 patients with small-size uveal melanomas (0.2–1.5 ml) were imaged on a combined whole-body PET/CT, a HR brain-PET, and a 1.5 T MRI. Static, contrast-enhanced FDG-PET/CT imaging was performed of head and torso with CT contrast enhancement. HR PET imaging was performed in dynamic mode 0–180 min post-injection of FDG. MRI imaging was performed using a high-resolution small-loop-coil placed over the eye in question with T2–3D-TSE and T1–3D-SE with 18 ml Gd-contrast. Patients had their eyes shaded during the scans. Lesion visibility on high-resolution FDGPET images was graded for confidence: 1: none, 2: suggestive, 3: clear. Mean tumour activity was calculated for summed image frames that resulted in confidence grades 2 and 3. Whole-body FDG-PET/CT images were reviewed for lesions. PET-MRI and PET/ CT-MRI images of the head were co-registered for potentially improved lesion delineation. Results: Whole-body FDG-PET/CT images of 3/3 patients were positive for uveal melanomas and negative for disseminated disease. HR FDG-PET was positive already in the early time frames. One patient exhibited rising tumour activity with increasing uptake time on FDG-PET. MRI images of the eye were co-registered successfully to FDG-PET/CT using a manual alignment approach. Conclusions: Small-size uveal melanomas can be detected with whole-body FDG-PET/CT. This feasibility study suggests the exploration of HR FDG-PET in order to provide additional diagnostic information on patients with uveal melanomas. First results support extended uptake times and high-sensitivity PET for improved tumour visibility. MRI/PET co-registration is feasible and provides correlated functional and anatomical information that may support alternative therapy regimens.
5

Suganuma, Yuta, Atsushi Teramoto, Kuniaki Saito, Hiroshi Fujita, Yuki Suzuki, Noriyuki Tomiyama, and Shoji Kido. "Hybrid Multiple-Organ Segmentation Method Using Multiple U-Nets in PET/CT Images." Applied Sciences 13, no. 19 (September 27, 2023): 10765. http://dx.doi.org/10.3390/app131910765.

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PET/CT can scan low-dose computed tomography (LDCT) images with morphological information and PET images with functional information. Because the whole body is targeted for imaging, PET/CT examinations are important in cancer diagnosis. However, the several images obtained by PET/CT place a heavy burden on radiologists during diagnosis. Thus, the development of computer-aided diagnosis (CAD) and technologies assisting in diagnosis has been requested. However, because FDG accumulation in PET images differs for each organ, recognizing organ regions is essential for developing lesion detection and analysis algorithms for PET/CT images. Therefore, we developed a method for automatically extracting organ regions from PET/CT images using U-Net or DenseUNet, which are deep-learning-based segmentation networks. The proposed method is a hybrid approach combining morphological and functional information obtained from LDCT and PET images. Moreover, pre-training using ImageNet and RadImageNet was performed and compared. The best extraction accuracy was obtained by pre-training ImageNet with Dice indices of 94.1, 93.9, 91.3, and 75.1% for the liver, kidney, spleen, and pancreas, respectively. This method obtained better extraction accuracy for low-quality PET/CT images than did existing studies on PET/CT images and was comparable to existing studies on diagnostic contrast-enhanced CT images using the hybrid method and pre-training.
6

Seiffert, Alexander P., Adolfo Gómez-Grande, Alberto Villarejo-Galende, Marta González-Sánchez, Héctor Bueno, Enrique J. Gómez, and Patricia Sánchez-González. "High Correlation of Static First-Minute-Frame (FMF) PET Imaging after 18F-Labeled Amyloid Tracer Injection with [18F]FDG PET Imaging." Sensors 21, no. 15 (July 30, 2021): 5182. http://dx.doi.org/10.3390/s21155182.

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Dynamic early-phase PET images acquired with radiotracers binding to fibrillar amyloid-beta (Aβ) have shown to correlate with [18F]fluorodeoxyglucose (FDG) PET images and provide perfusion-like information. Perfusion information of static PET scans acquired during the first minute after radiotracer injection (FMF, first-minute-frame) is compared to [18F]FDG PET images. FMFs of 60 patients acquired with [18F]florbetapir (FBP), [18F]flutemetamol (FMM), and [18F]florbetaben (FBB) are compared to [18F]FDG PET images. Regional standardized uptake value ratios (SUVR) are directly compared and intrapatient Pearson’s correlation coefficients are calculated to evaluate the correlation of FMFs to their corresponding [18F]FDG PET images. Additionally, regional interpatient correlations are calculated. The intensity profiles of mean SUVRs among the study cohort (r = 0.98, p < 0.001) and intrapatient analyses show strong correlations between FMFs and [18F]FDG PET images (r = 0.93 ± 0.05). Regional VOI-based analyses also result in high correlation coefficients. The FMF shows similar information to the cerebral metabolic patterns obtained by [18F]FDG PET imaging. Therefore, it could be an alternative to the dynamic imaging of early phase amyloid PET and be used as an additional neurodegeneration biomarker in amyloid PET studies in routine clinical practice while being acquired at the same time as amyloid PET images.
7

Lee, Giljae, Hwunjae Lee, and Gyehwan Jin. "Analysis of Fitting Degree of MRI and PET Images in Simultaneous MRPET Images by Machine Learning Neural Networks." ScholarGen Publishers 3, no. 1 (December 28, 2020): 43–61. http://dx.doi.org/10.31916/sjmi2020-01-05.

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Simultaneous MR-PET imaging is a fusion of MRI using various parameters and PET images using various nuclides. In this paper, we performed analysis on the fitting degree between MRI and simultaneous MR-PET images and between PET and simultaneous MR-PET images. For the fitness analysis by neural network learning, feature parameters of experimental images were extracted by discrete wavelet transform (DWT), and the extracted parameters were used as input data to the neural network. In comparing the feature values extracted by DWT for each image, the horizontal and vertical low frequencies showed similar patterns, but the patterns were different in the horizontal and vertical high frequency and diagonal high frequency regions. In particular, the signal value was large in the T1 and T2 weighted images of MRI. Neural network learning results for fitting degree analysis were as follows. 1. T1-weighted MRI and simultaneous MR-PET image fitting degree: Regression (R) values were found to be Training 0.984, Validation 0.844, and Testing 0.886. 2. Dementia-PET image and Simultaneous MR-PET Image fitting degree: R values were found to be Training 0.970, Validation 0.803, and Testing 0.828. 3. T2-weighted MRI and concurrent MR-PET image fitting degree: R values were found to be Training 0.999, Validation 0.908, and Testing 0.766. 4. Brain tumor-PET image and Simultaneous MR-PET image fitting degree: R values were found to be Training 0.999, Validation 0.983, and Testing 0.876. An R value closer to 1 indicates more similarity. Therefore, each image fused in the simultaneous MR-PET images verified in this study was found to be similar. Ongoing study of images acquired with pulse sequences other than the weighted images in the MRI is needed. These studies may establish a useful protocol for the acquisition of simultaneous MR-PET images.
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Couto, Pedro, Telmo Bento, Humberto Bustince, and Pedro Melo-Pinto. "Positron Emission Tomography Image Segmentation Based on Atanassov’s Intuitionistic Fuzzy Sets." Applied Sciences 12, no. 10 (May 11, 2022): 4865. http://dx.doi.org/10.3390/app12104865.

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In this paper, we present an approach to fully automate tumor delineation in positron emission tomography (PET) images. PET images play a major role in medicine for in vivo imaging in oncology (PET images are used to evaluate oncology patients, detecting emitted photons from a radiotracer localized in abnormal cells). PET image tumor delineation plays a vital role both in pre- and post-treatment stages. The low spatial resolution and high noise characteristics of PET images increase the challenge in PET image segmentation. Despite the difficulties and known limitations, several image segmentation approaches have been proposed. This paper introduces a new unsupervised approach to perform tumor delineation in PET images using Atanassov’s intuitionistic fuzzy sets (A-IFSs) and restricted dissimilarity functions. Moreover, the implementation of this methodology is presented and tested against other existing methodologies. The proposed algorithm increases the accuracy of tumor delineation in PET images, and the experimental results show that the proposed method outperformed all methods tested.
9

Li, Hui, Chao Gao, Yingying Sun, Aojie Li, Wang Lei, Yuming Yang, Ting Guo, et al. "Radiomics Analysis to Enhance Precise Identification of Epidermal Growth Factor Receptor Mutation Based on Positron Emission Tomography Images of Lung Cancer Patients." Journal of Biomedical Nanotechnology 17, no. 4 (April 1, 2021): 691–702. http://dx.doi.org/10.1166/jbn.2021.3056.

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How to recognize precisely epidermal growth factor receptor (EGFR) mutation in lung cancer patients owns great clinical requirement. In this study, 1575 radiomics features were extracted from PET images of 75 lung cancer patients based on contrast agents such as 18F-MPG and 18F-FDG. The Mann-Whitney U test was used for single factor analysis, the Least Absolute Shrinkage and Selection Operator (Lasso) Regression was used for feature screening, then the radiomics classification models were established by using support vector machines and ten-fold cross-validation, and were used to identify EGFR mutation in primary lung cancers and metastasis lung cancers, accuracy based on 18F-MPG PET images are respectively 90% for primary lung cancers, and 89.66% for metastasis lung cancers, accuracy based on 18F-FDG PET images are respectively 76% for primary lung cancers and 82.75% for metastasis lung cancers. The area under the curves (AUC) based on 18F-MPG PET images are respectively 0.94877 for primary lung cancers, and 0.91775 for metastasis lung cancers, AUC based on 18F-FDG PET images are respectively 0.87374 for primary lung cancers, and 0.82251 for metastasis lung cancers. In conclusion, both 18F-MPG PET images and 18F-FDG PET images combined with established classification models can identify EGFR mutation, but 18F-MPG PET images have more precisely than 18F-FDG PET images, own clinical translational prospects.
10

Petryakova, A. V., L. A. Chipiga, M. S. Tlostanova, A. A. Ivanova, D. A. Vazhenina, A. A. Stanzhevsky, D. V. Ryzhkova, et al. "Method of Experts’ Quality Evaluation of the PET Images of the Patients." MEDICAL RADIOLOGY AND RADIATION SAFETY 68, no. 1 (February 2023): 78–85. http://dx.doi.org/10.33266/1024-6177-2023-68-1-78-85.

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Purpose: To develop the method of experts’ quality evaluation of the PET images as an additional quality control method for accurate, comparable, and reproducible PET diagnostics results, and to conduct image quality evaluation in different PET departments used this method. Material and methods: 60 PET images (without CT) of the patients who underwent whole body PET/CT with 18F-FDG were collected from 12 PET/CT scanners in 9 PET departments. Experts’ quality evaluation was conducted with questioning of the experts. Each expert evaluated the image quality by five-point scale and filled out the special form which include three image quality criteria: image clarity, artefacts, and general image quality. There were 28 experts from 8 different PET departments who have work experience in radiology from 1 to 32 years. The results of experts’ quality evaluation of the PET images were examined for correlations with parameters of acquisition and reconstruction protocols, examination methods. The results were also examined for dependance of subjective factors such as work experience and work conditions of experts. The minimum required number of experts were defined. The results were analyzed used statistical methods. Results: The PET images obtained by 8 PET/CT scanners had mean quality value more than 4 points (good quality). PET/CT scanners, which had the lowest quality value, have the obsolete or unusual settings and reconstruction parameters. The correlations between experts’ quality evaluation of the PET images and acquisition parameters (acquisition time per bed, multiplication of injected activity and acquisition time per bed), and examination methods (injected activity and uptake time) were established. The results of experts’ quality evaluation of the PET images were dependent on work experience and work conditions of experts. Conclusion: The method of experts’ quality evaluation of the PET images of the patients based on the questioning of the experts working in PET was developed and demonstrated in the current study. The results showed this method has the potential to compare the PET images obtained by different acquisition and reconstruction protocols, and it can be applied during the optimization of examination method and for the determination of obsolete and unusual settings of PET/CT. Experts’ evaluation of the PET images should include the opinion of at least six experts with different work experience in PET from several PET departments.
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Journal articles Dissertations / Theses Books

Dissertations / Theses on the topic "Images PET":

1

Cruz, Cavalcanti Yanna. "Factor analysis of dynamic PET images." Thesis, Toulouse, INPT, 2018. http://www.theses.fr/2018INPT0078/document.

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La tomographie par émission de positrons (TEP) est une technique d'imagerie nucléaire noninvasive qui permet de quantifier les fonctions métaboliques des organes à partir de la diffusion d'un radiotraceur injecté dans le corps. Alors que l'imagerie statique est souvent utilisée afin d'obtenir une distribution spatiale de la concentration du traceur, une meilleure évaluation de la cinétique du traceur est obtenue par des acquisitions dynamiques. En ce sens, la TEP dynamique a suscité un intérêt croissant au cours des dernières années, puisqu'elle fournit des informations à la fois spatiales et temporelles sur la structure des prélèvements de traceurs en biologie \textit{in vivo}. Les techniques de quantification les plus efficaces en TEP dynamique nécessitent souvent une estimation de courbes temps-activité (CTA) de référence représentant les tissus ou une fonction d'entrée caractérisant le flux sanguin. Dans ce contexte, de nombreuses méthodes ont été développées pour réaliser une extraction non-invasive de la cinétique globale d'un traceur, appelée génériquement analyse factorielle. L'analyse factorielle est une technique d'apprentissage non-supervisée populaire pour identifier un modèle ayant une signification physique à partir de données multivariées. Elle consiste à décrire chaque voxel de l'image comme une combinaison de signatures élémentaires, appelées \textit{facteurs}, fournissant non seulement une CTA globale pour chaque tissu, mais aussi un ensemble des coefficients reliant chaque voxel à chaque CTA tissulaire. Parallèlement, le démélange - une instance particulière d'analyse factorielle - est un outil largement utilisé dans la littérature de l'imagerie hyperspectrale. En imagerie TEP dynamique, elle peut être très pertinente pour l'extraction des CTA, puisqu'elle prend directement en compte à la fois la non-négativité des données et la somme-à-une des proportions de facteurs, qui peuvent être estimées à partir de la diffusion du sang dans le plasma et les tissus. Inspiré par la littérature de démélange hyperspectral, ce manuscrit s'attaque à deux inconvénients majeurs des techniques générales d'analyse factorielle appliquées en TEP dynamique. Le premier est l'hypothèse que la réponse de chaque tissu à la distribution du traceur est spatialement homogène. Même si cette hypothèse d'homogénéité a prouvé son efficacité dans plusieurs études d'analyse factorielle, elle ne fournit pas toujours une description suffisante des données sousjacentes, en particulier lorsque des anomalies sont présentes. Pour faire face à cette limitation, les modèles proposés ici permettent un degré de liberté supplémentaire aux facteurs liés à la liaison spécifique. Dans ce but, une perturbation spatialement variante est introduite en complément d'une CTA nominale et commune. Cette variation est indexée spatialement et contrainte avec un dictionnaire, qui est soit préalablement appris ou explicitement modélisé par des non-linéarités convolutives affectant les tissus de liaisons non-spécifiques. Le deuxième inconvénient est lié à la distribution du bruit dans les images PET. Même si le processus de désintégration des positrons peut être décrit par une distribution de Poisson, le bruit résiduel dans les images TEP reconstruites ne peut généralement pas être simplement modélisé par des lois de Poisson ou gaussiennes. Nous proposons donc de considérer une fonction de coût générique, appelée $\beta$-divergence, capable de généraliser les fonctions de coût conventionnelles telles que la distance euclidienne, les divergences de Kullback-Leibler et Itakura-Saito, correspondant respectivement à des distributions gaussiennes, de Poisson et Gamma. Cette fonction de coût est appliquée à trois modèles d'analyse factorielle afin d'évaluer son impact sur des images TEP dynamiques avec différentes caractéristiques de reconstruction
Thanks to its ability to evaluate metabolic functions in tissues from the temporal evolution of a previously injected radiotracer, dynamic positron emission tomography (PET) has become an ubiquitous analysis tool to quantify biological processes. Several quantification techniques from the PET imaging literature require a previous estimation of global time-activity curves (TACs) (herein called \textit{factors}) representing the concentration of tracer in a reference tissue or blood over time. To this end, factor analysis has often appeared as an unsupervised learning solution for the extraction of factors and their respective fractions in each voxel. Inspired by the hyperspectral unmixing literature, this manuscript addresses two main drawbacks of general factor analysis techniques applied to dynamic PET. The first one is the assumption that the elementary response of each tissue to tracer distribution is spatially homogeneous. Even though this homogeneity assumption has proven its effectiveness in several factor analysis studies, it may not always provide a sufficient description of the underlying data, in particular when abnormalities are present. To tackle this limitation, the models herein proposed introduce an additional degree of freedom to the factors related to specific binding. To this end, a spatially-variant perturbation affects a nominal and common TAC representative of the high-uptake tissue. This variation is spatially indexed and constrained with a dictionary that is either previously learned or explicitly modelled with convolutional nonlinearities affecting non-specific binding tissues. The second drawback is related to the noise distribution in PET images. Even though the positron decay process can be described by a Poisson distribution, the actual noise in reconstructed PET images is not expected to be simply described by Poisson or Gaussian distributions. Therefore, we propose to consider a popular and quite general loss function, called the $\beta$-divergence, that is able to generalize conventional loss functions such as the least-square distance, Kullback-Leibler and Itakura-Saito divergences, respectively corresponding to Gaussian, Poisson and Gamma distributions. This loss function is applied to three factor analysis models in order to evaluate its impact on dynamic PET images with different reconstruction characteristics
2

Batty, Stephen. "Content based retrieval of PET neurological images." Thesis, Middlesex University, 2004. http://eprints.mdx.ac.uk/9770/.

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Medical image management has posed challenges to many researchers, especially when the images have to be indexed and retrieved using their visual content that is meaningful to clinicians. In this study, an image retrieval system has been developed for 3D brain PET (Position emission tomography) images. It has been found that PET neurological images can be retrieved based upon their diagnostic status using only data pertaining to their content, and predominantly the visual content. During the study PET scans are spatially normalized, using existing techniques, and their visual data is quantified. The mid-sagittal-plane of each individual 3D PET scan is found and then utilized in the detection of abnormal asymmetries, such as tumours or physical injuries. All the asymmetries detected are referenced to the Talairarch and Tournoux anatomical atlas. The Cartesian co- ordinates in Talairarch space, of detected lesion, are employed along with the associated anatomical structure(s) as the indices within the content based image retrieval system. The anatomical atlas is then also utilized to isolate distinct anatomical areas that are related to a number of neurodegenerative disorders. After segmentation of the anatomical regions of interest algorithms are applied to characterize the texture of brain intensity using Gabor filters and to elucidate the mean index ratio of activation levels. These measurements are combined to produce a single feature vector that is incorporated into the content based image retrieval system. Experimental results on images with known diagnoses show that physical lesions such as head injuries and tumours can be, to a certain extent, detected correctly. Images with correctly detected and measured lesion are then retrieved from the database of images when a query pertains to the measured locale. Images with neurodegenerative disorder patterns have been indexed and retrieved via texture-based features. Retrieval accuracy is increased, for images from patients diagnosed with dementia, by combining the texture feature and mean index ratio value.
3

Pavarin, Alice. "Comparison of textural features in PET images: a phantom study." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018.

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La radiomica può essere definita come l'analisi quantitativa di immagini radiologiche derivanti, per esempio, da risonanze magnetiche e PET. L'analisi quantitativa avviene tramite software attraverso l'estrazione di features. L'analisi delle features è importante perché permette di fare previsioni, per esempio, sulla capacità del soggetto di rispondere positivamente alle cure previste o perché può aiutare nell'individuazione automatica della massa tumorale nell'immagine. Inoltre tale analisi si affianca al lavoro visivo di studio dell'immagine fatto dall'oncologo o dal radiologo. Il valore delle features cambia in base a diversi fattori, come per esempio lo scanner usato o le modalità di ricostruzione dell'immagine. Appare quindi importante, in ogni singola indagine, capire quali features sono le più robuste e quali le più variabili perché dal loro valore si dedurranno elementi diagnostici relativi all'oggetto studiato. In questa tesi si è analizzata la robustezza di 11 features in immagini PET al variare dei parametri di ricostruzione dell'immagine. Le immagini considerate provengono dallo IEO di Milano. Si sono analizzati 9 datasets e per ogni feature si è valutata la robustezza al variare dei parametri di ricostruzione, al variare delle ROI (regioni di interesse, tipicamente le masse tumorali, su cui si concentra lo studio delle features), al variare della grandezza della ROI e della grandezza delle sfere da cui le ROI sono state estratte. Inoltre si è calcolata la robustezza delle features fissando il metodo di ricostruzione di default e si è indagata la stabilità dei metodi valutando i valori delle singole features su 15 ROI della stessa grandezza (5 per ogni sfera analizzata nel fantoccio). Si è notato che alcune features (come l'entropia e l'entropia-GLCM) appaiono più stabili mentre altre features sono assai volatili (come la varianza). Si è visto inoltre che la variabilità delle features aumenta al variare della grandezza della ROI considerata.
4

Yu, Chin-Lung. "Methods for automated analysis of small-animal PET images." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1580851181&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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RAPISARDA, EUGENIO. "Improvements in quality and quantification of 3D PET images." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2012. http://hdl.handle.net/10281/28157.

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The spatial resolution of Positron Emission Tomography is conditioned by several physical factors, which can be taken into account by using a global Point Spread Function (PSF). In this thesis a spatially variant (radially asymmetric) PSF implementation in the image space of a 3D Ordered Subsets Expectation Maximization (OSEM) algorithm is proposed. Two different scanners were considered, without and with Time Of Flight (TOF) capability. The PSF was derived by fitting some experimentally acquired images of a Na22 cylindrical source reconstructed with an OSEM algorithm. The fitting function took into account the post-filter applied on the images, the actual position of the point source, the source dimensions and the intrinsic discretization along the axial direction due to the finite dimensions of the slices. The proposed method of measurement was also validated and demonstrated its good accuracy in building the PSF model, justifying its use. The implementation of the PSF consisted in a redefinition of the projector and backprojector of the 3D OSEM algorithm. The continuous model of the PSF has been discretized by calculating its integral for each voxel in the image, allowing for a better adaptive implementation for each specific reconstruction FOV and pixel size. The explicit expression for the transposed PSF operator was also derived, showing that - in the spatially variant case - this does not coincide with the transpose of the PSF kernel. The PSF was tested on some phantom and clinical data: the results showed improved quantitative accuracy, spatial resolution and image quality; furthermore, the combined use of TOF and PSF appeared to allow them to take advantage of each other, leading to the best results. Unfortunately, a common effect of iterative reconstruction techniques is the increase of noise as iterations proceed, due to the ill-posed nature of the reconstruction problem. This is in contrast with the requirements of a PSF-aware algorithm, since the speed of convergence is lower than in non-PSF algorithms and, therefore, more iterations would be required to reach a sufficient convergence. Another important effect observed in PSF-based reconstructions is the enhancement of regions with sharp intensity transitions. In this thesis it was demonstrated to be strongly related to the implementation of the spatial resolution recovery and, even in presence of a perfectly matched kernel, unavoidable unless an unpractical number of iterations is used. Regularization techniques have been demonstrated to be useful for taking noise under control during the reconstruction and improving the benefits from the use of the PSF information by increasing the number of iterations used. In particular, in this thesis a Bayesian variational regularization strategy has been tested and employed. Two good candidates for the use in PET practice are the Huber (or Gauss-Total Variation) and the generalized p-Gaussian priors. In this thesis a modification of the p-Gaussian prior was proposed to maintain the smoothing effect for low gradients (i.e. in background regions) and to reduce the spatial resolution loss, while retaining "natural" transitions and appearance in the image. The considered priors depend on some regularization parameters. In this thesis a figure of merit, taking into account both the qualitative and the quantitative content, was proposed to evaluate the global "detectability" of a lesion. The validation of this detectability index showed a very good correlation with the human response and, thus, justified its use to set the regularization parameters. The regularization parameters were then determined by maximizing the detectability index for each prior. This optimization was performed for a sphere with diameter 10 mm and 10 OSEM iterations. The validation of the proposed modifications was quantitative on data acquired with a NEMA IEC Body Phantom and qualitative on data relative to two oncological patients and consisted of a comparison between the standard reconstruction algorithms, the proposed algorithm, the results obtained with the p-Gaussian prior and with Gauss-Total Variation. This comparison showed an effective control of noise (but with natural appearance of the image) by the proposed prior with a contemporary good preservation of spatial resolution, contrast and definition of the activity distribution. Moreover, the proposed prior was shown to be able also to take the edge artefact under control, drastically reducing the overshoots originating at large transitions in the image. Positive results were obtained also when the regularization strategy was used in conjunction with the TOF information, suggesting a possible future employment in the PET reconstruction framework.
6

Jonsson, Sofia. "Evaluation of Methods for Obtaining an Image Derived Input Function from Dynamic PET-images." Thesis, Umeå universitet, Institutionen för fysik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-124426.

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Dynamic PET is a technique to follow the uptake kinetics of radioactive labelled molecules in the human body. The kinetic behaviour may be analysed to acquire parameters, such as perfusion of blood to tissue, with the knowledge of the blood activity time curve (also called input function). This is usually measured by continuous sampling by letting the blood flow through a detector but this is both burdensome and not without risk to the patient \cite{Feng2012}. Instead, an alternative method would be to determine the input function from the PET-images and thus get an image derived input function (IDIF). In this master thesis evaluation of analytical models, tested on both experimental sampled data of a phantom and on data from actual patients, were used to determine the IDIF from small blood vessels. A phantom was built from plastic tubes and plexiglass to test and evaluate different methods. In order to get a correct IDIF one needs to correct for partial volume effect (PVE) which in small volumes of interest (VOI) gives apparent lower activity than reality. The correction can be done in a few different ways but this paper focuses on multi-target correction (MTC) which uses two or more VOIs to obtain the true activity value \cite{PVE_corrections}. The method was evaluated using data from phantom measurements where the activity was known and could be used as a reference. The phantom was constructed using ten tubes of different dimensions, a plexiglass holder and a plastic box. The result from the PVE correction turned out to be highly dependent on accurately knowing the diameter. However, when the diameter of the VOI matched the diameter of the tube the error of activity was, on average, less than 6.1 \% (less than 4.9 \% for tubes larger than 6 mm in diameter) when evaluating the measured phantom data without added background. Also, varying backgrounds were added creating different contrasts between the tubes and background. When adding background the noise in the image is increased and the results from the PVCs, when using the most accurate diameter, were less accurate with a total average activity error of 17.9 \% (11.1 \% for diameters larger than 6 mm and 22.4 \% for diameters smaller than 6 mm). As a conclusion, the size of the blood vessel needs to be accurately known in order for the PVC to give the most accurate result. Also using vessels larger than 6 mm is beneficial.
7

Sims, John Andrew. "Directional analysis of cardiac left ventricular motion from PET images." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/3/3142/tde-05092017-093020/.

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Quantification of cardiac left ventricular (LV) motion from medical images provides a non-invasive method for diagnosing cardiovascular disease (CVD). The proposed study continues our group\'s line of research in quantification of LV motion by applying optical flow (OF) techniques to quantify LV motion in gated Rubidium Chloride-82Rb (82Rb) and Fluorodeoxyglucose-18F (FDG) PET image sequences. The following challenges arise from this work: (i) the motion vector field (MVF) should be made as accurate as possible to maximise sensitivity and specificity; (ii) the MVF is large and composed of 3D vectors in 3D space, making visual extraction of information for medical diagnosis dffcult by human observers. Approaches to improve the accuracy of motion quantification were developed. While the volume of interest is the region of the MVF corresponding to the LV myocardium, non-zero values of motion exist outside this volume due to artefacts in the motion detection method or from neighbouring structures, such as the right ventricle. Improvements in accuracy can be obtained by segmenting the LV and setting the MVF to zero outside the LV. The LV myocardium was automatically segmented in short-axis slices using the Hough circle transform to provide an initialisation to the distance regularised level set evolution algorithm. Our segmentation method attained Dice similarity measure of 93.43% when tested over 395 FDG slices, compared with manual segmentation. Strategies for improving OF performance at motion boundaries were investigated using spatially varying averaging filters, applied to synthetic image sequences. Results showed improvements in motion quantification accuracy using these methods. Kinetic Energy Index (KEf), an indicator of cardiac motility, was used to assess 63 individuals with normal and altered/low cardiac function from a 82Rb PET image database. Sensitivity and specificity tests were performed to evaluate the potential of KEf as a classifier of cardiac function, using LV ejection fraction as gold standard. A receiver operating characteristics curve was constructed, which provided an area under the curve of 0.906. Analysis of LV motion can be simplified by visualisation of directional motion field components, namely radial, rotational (or circumferential) and linear, obtained through automated decomposition. The Discrete Helmholtz Hodge Decomposition (DHHD) was used to generate these components in an automated manner, with a validation performed using synthetic cardiac motion fields from the Extended Cardiac Torso phantom. Finally, the DHHD was applied to OF fields from gated FDG images, allowing an analysis of directional components from an individual with normal cardiac function and a patient with low function and a pacemaker fitted. Motion field quantification from PET images allows the development of new indicators to diagnose CVDs. The ability of these motility indicators depends on the accuracy of the quantification of movement, which in turn can be determined by characteristics of the input images, such as noise. Motion analysis provides a promising and unprecedented approach to the diagnosis of CVDs.
A quantificação do movimento cardíaco do ventrículo esquerdo (VE) a partir de imagens médicas fornece um método não invasivo para o diagnóstico de doenças cardiovasculares (DCV). O estudo aqui proposto continua na mesma linha de pesquisa do nosso grupo sobre quantificação do movimento do VE por meio de técnicas de fluxo óptico (FO), aplicando estes métodos para quantificar o movimento do VE em sequências de imagens associadas às substâncias de cloreto de rubídio-82Rb (82Rb) e fluorodeoxiglucose-18F (FDG) PET. Com a extração dos campos vetoriais surgiram os seguintes desafios: (i) o campo vetorial de movimento (motion vector field, MVF) deve ser feito da forma mais precisa possível para maximizar a sensibilidade e especificidade; (ii) o MVF é extenso e composto de vetores 3D no espaço 3D, dificultando a análise visual de informações por observadores humanos para o diagnóstico médico. Foram desenvolvidas abordagens para melhorar a precisão da quantificação de movimento, considerando que o volume de interesse seja a região do MVF correspondente ao miocárdio do VE, em que valores de movimento não nulos existem fora deste volume devido aos artefatos do método de detecção de movimento ou de estruturas vizinhas, como o ventrículo direito. As melhorias na precisão foram obtidas segmentando o VE e ajustando os valores de MVF para zero fora do VE. O miocárdio VE foi segmentado automaticamente em fatias de eixo curto usando a Transformada de Hough na detecção de círculos para fornecer uma inicialização ao algoritmo de curvas de nível, um tipo de modelo deformável. A segmentação automática do VE atingiu 93,43% de medida de similaridade Dice, quando foi testado em 395 fatias de eixo menor de FDG, comparado com a segmentação manual. Estratégias para melhorar o desempenho do algoritmo OF nas bordas de movimento foram investigadas usando spatially varying averaging filters, aplicados em seqüências de imagens sintéticas. Os resultados mostraram melhorias na precisão de quantificação de movimento utilizando estes métodos. O Índice de Energia Cinética (KEf), um indicador de motilidade cardíaca, foi utilizado para avaliar 63 sujeitos com função cardíaca normal e alterada / baixa de uma base de dados de imagens PET de 82Rb. Foram realizados testes de sensibilidade e especificidade para avaliar o potencial de KEf para classificar a função cardíaca, utilizando a fração de ejeção do VE como padrão ouro. Foi construída uma curva ROC, que proporcionou uma área sob a curva de 0,906. A análise do movimento do VE pode ser simplificada pela visualização de componentes de campo de movimento direcional, ou seja, radial, rotacional (ou circunferencial) e linear, obtidos por decomposição automatizada. A decomposição discreta de Helmholtz Hodge (DHHD) foi utilizada para gerar estes componentes de forma automatizada, com uma validação utilizando campos de movimento cardíaco sintéticos a partir do conjunto Extended Cardiac Torso Phantom. Finalmente, o método DHHD foi aplicado a campos de FO, criado a partir de imagens FDG, permitindo uma análise de componentes direcionais de um indivíduo com função cardíaca normal e um paciente com baixa função e utilizando um marca-passo. A quantificação do campo de movimento a partir de imagens PET possibilita o desenvolvimento de novos indicadores para diagnosticar DCVs. A capacidade destes indicadores de motilidade depende na precisão da quantificação de movimento que, por sua vez, pode ser determinado por características das imagens de entrada como ruído. A análise de movimento fornece um promissor e sem precedente método para o diagnóstico de DCVs.
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Farinha, Ricardo Jorge Pires Correia. "Segmentation of striatal brain structures from high resolution pet images." Master's thesis, FCT - UNL, 2008. http://hdl.handle.net/10362/2036.

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Dissertation presented at the Faculty of Science and Technology of the New University of Lisbon in fulfillment of the requirements for the Masters degree in Electrical Engineering and Computers
We propose and evaluate fully automatic segmentation methods for the extraction of striatal brain surfaces (caudate, putamen, ventral striatum and white matter), from high resolution positron emission tomography (PET) images. In the preprocessing steps, both the right and the left striata were segmented from the high resolution PET images. This segmentation was achieved by delineating the brain surface, finding the plane that maximizes the reflective symmetry of the brain (mid-sagittal plane) and, finally, extracting the right and left striata from both hemisphere images. The delineation of the brain surface and the extraction of the striata were achieved using the DSM-OS (Surface Minimization – Outer Surface) algorithm. The segmentation of striatal brain surfaces from the striatal images can be separated into two sub-processes: the construction of a graph (named “voxel affinity matrix”) and the graph clustering. The voxel affinity matrix was built using a set of image features that accurately informs the clustering method on the relationship between image voxels. The features defining the similarity of pairwise voxels were spatial connectivity, intensity values, and Euclidean distances. The clustering process is treated as a graph partition problem using two methods, a spectral (multiway normalized cuts) and a non-spectral (weighted kernel k-means). The normalized cuts algorithm relies on the computation of the graph eigenvalues to partition the graph into connected regions. However, this method fails when applied to high resolution PET images due to the high computational requirements arising from the image size. On the other hand, the weighted kernel k-means classifies iteratively, with the aid of the image features, a given data set into a predefined number of clusters. The weighted kernel k-means and the normalized cuts algorithm are mathematically similar. After finding the optimal initial parameters for the weighted kernel k-means for this type of images, no further tuning is necessary for subsequent images. Our results showed that the putamen and ventral striatum were accurately segmented, while the caudate and white matter appeared to be merged in the same cluster. The putamen was divided in anterior and posterior areas. All the experiments resulted in the same type of segmentation, validating the reproducibility of our results.
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Bieth, Marie. "Kinetic analysis and inter-subject registration of brain PET images." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=119738.

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Positron emission tomography (PET) imaging is becoming increasingly popular for understanding brain function. This thesis addresses two problems related to PET images: binding potential (BP) computation and pairwise PET image registration. We first investigate the influence of several computational choices on the calculation of binding potential maps in brain PET. Our work uses simulated data and allows us to provide some benchmarks for the choices to make for BP computation, which is an important step towards fully automated MR independent BP estimation. We then introduce a new method for pairwise dynamic PET image registration that is derived from the 3D diffeomorphic log-demons algorithm, and demonstrate an improvement over existing methods. We also present a high-resolution [11C]raclopride PET template built from 35 subjects scanned on the High Resolution Research Tomograph. As this is the highest resolution PET scanner available at the time, to the best of our knowledge, this template is the best quality representation of a PET [11C]raclopride image produced to date.
L'imagerie à émission de positrons est de plus en plus utilisée pour comprendre le fonctionnement du cerveau. Ce mémoire aborde deux sujets liés àces images: le calcul du potentiel de liaison et l'alignement de deux images. Nous étudions tout d'abord l'influence de certains choix d'implémentation sur les estimations de potentiel de liaison. Ces travaux effectués sur des données simulées nous permettent de donner des points de repère concernant les choix à faire pour calculer le potentiel de liaison, ce qui constitue un pas important vers un calcul du potentiel de liaison entièrement automatisé etindépendant d'images à résonance magnétique. Nous introduisons ensuite une nouvelle méthode pour l'alignement de deux images de tomographie à émission de positrons. Cette méthode est adaptée de l'algorithme des log-démons difféomorphiques 3D. Nous montrons que notre méthode donne de meilleurs résultats que des méthodes existantes. Nous présentons aussi un modèle de haute résolution pour l'imagerie à émissionde positrons utilisant la [11C]raclopride. Ce modèle est construit à partir de 35sujets scannés sur le tomographe de recherche à haute résolution (High Resolution Research Tomograph). Comme il s'agit du tomographe de plus haute résolution disponible à ce jour, à notre connaissance, notre modèle est l'image de raclopride de plus haute résolution jamais produite.
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Wang, Jiali. "Motion Correction Algorithm of Lung Tumors for Respiratory Gated PET Images." FIU Digital Commons, 2009. http://digitalcommons.fiu.edu/etd/96.

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Respiratory gating in lung PET imaging to compensate for respiratory motion artifacts is a current research issue with broad potential impact on quantitation, diagnosis and clinical management of lung tumors. However, PET images collected at discrete bins can be significantly affected by noise as there are lower activity counts in each gated bin unless the total PET acquisition time is prolonged, so that gating methods should be combined with imaging-based motion correction and registration methods. The aim of this study was to develop and validate a fast and practical solution to the problem of respiratory motion for the detection and accurate quantitation of lung tumors in PET images. This included: (1) developing a computer-assisted algorithm for PET/CT images that automatically segments lung regions in CT images, identifies and localizes lung tumors of PET images; (2) developing and comparing different registration algorithms which processes all the information within the entire respiratory cycle and integrate all the tumor in different gated bins into a single reference bin. Four registration/integration algorithms: Centroid Based, Intensity Based, Rigid Body and Optical Flow registration were compared as well as two registration schemes: Direct Scheme and Successive Scheme. Validation was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System. Iterations were conducted on different size simulated tumors and different noise levels. Static tumors without respiratory motion were used as gold standard; quantitative results were compared with respect to tumor activity concentration, cross-correlation coefficient, relative noise level and computation time. Comparing the results of the tumors before and after correction, the tumor activity values and tumor volumes were closer to the static tumors (gold standard). Higher correlation values and lower noise were also achieved after applying the correction algorithms. With this method the compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become fast and precise.
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Books on the topic "Images PET":

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Panetta, Daniele, and Niccoló Camarlinghi. 3D Image Reconstruction for CT and PET. Boca Raton : CRC Press, 2020. | Series: Focus series in medical physics and biomedical engineering: CRC Press, 2020. http://dx.doi.org/10.1201/9780429270239.

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Waroquier, Henry de. Henry de Waroquier, images de Bretagne. Paris: Somogy, 2000.

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Sarsanedas, Jordi. Paraules per a unes imatges. Barcelona [Spain]: Publicacions de l'Abadia de Montserrat, 2004.

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Riera, Carme. Mallorca, imatges per la felicitat. Palma de Mallorca: Edicions de Turisme Cultural, Illes Balears, 2000.

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Russ, Nadia. How to draw NeoPopRealism ink images: Basics. New York: NeoPopRealism, 2011.

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Moretti, Giampiero. Per immagini: Esercizi di ermeneutica sensibile. Bergamo: Moretti & Vitali, 2012.

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Guttuso, Fabio Carapezza. Renato Guttuso: Biografia per immagini = biography through images. Troina: Città aperta edizioni, 2009.

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Ferrari, Federico. L'insieme vuoto: Per una pragmatica dell'immagine. Monza: Johan & Levi, 2013.

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Fanti, Stefano, Mohsen Farsad, and Luigi Mansi, eds. PET-CT Beyond FDG A Quick Guide to Image Interpretation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-93909-2.

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Fanti, Stefano. PET-CT beyond FDG: A quick guide to image interpretation. Berlin: Springer, 2010.

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Book chapters on the topic "Images PET":

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Knorr, U., Y. Huang, G. Schlaug, R. J. Seitz, and H. Steinmetz. "High Resolution PET Images through REDISTRIBUTION." In Computer Assisted Radiology / Computergestützte Radiologie, 517–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-49351-5_85.

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Kang, Jiayin, Yaozong Gao, Yao Wu, Guangkai Ma, Feng Shi, Weili Lin, and Dinggang Shen. "Prediction of Standard-Dose PET Image by Low-Dose PET and MRI Images." In Machine Learning in Medical Imaging, 280–88. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10581-9_35.

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Runge, Val M., and Johannes T. Heverhagen. "Integrated Whole-Body MR-PET." In The Physics of Clinical MR Taught Through Images, 300–303. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85413-3_137.

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Bastiaens, Koen, Paul Desmedt, and Ignace Lemahieu. "Parallel Maximum Entropy Reconstruction of PET Images." In Maximum Entropy and Bayesian Methods, 213–19. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-015-8729-7_17.

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Huang, Y., U. Knorr, H. Steinmetz, and R. J. Seitz. "Accurate Alignment and Reslicing of PET Images." In Computer Assisted Radiology / Computergestützte Radiologie, 788. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-49351-5_163.

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Plets, P., J. Nuyts, P. Dupont, and P. Suetens. "Registration of PET-Images Using Template Matching." In Computer Assisted Radiology / Computergestützte Radiologie, 509–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-49351-5_84.

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Huang, Ling, Su Ruan, Pierre Decazes, and Thierry Denœux. "Evidential Segmentation of 3D PET/CT Images." In Belief Functions: Theory and Applications, 159–67. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88601-1_16.

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Oldan, Jorge Daniel. "Review of PET/CT Images in Melanoma and Sarcoma: False Positives, False Negatives, and Pitfalls." In PET/CT and PET/MR in Melanoma and Sarcoma, 107–29. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60429-5_5.

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Cataldo, Sol A., Florencia Sarmiento Laspiur, and Martín A. Belzunce. "Automated PET Quantification of [18F]FDG PET Images for Neurodegenerative Disorders Research." In IFMBE Proceedings, 395–403. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-61973-1_37.

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Xu, Guofan. "18F-Fluoride Imaging: Atlas of Interesting Images (Images with Specific Teaching Points, Tracer, Technique, and Pitfalls)." In Sodium Fluoride PET/CT in Clinical Use, 61–68. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23577-2_8.

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Conference papers on the topic "Images PET":

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Davis, P. B., and M. A. Abidi. "Enhancement of PET Images." In 1989 Medical Imaging, edited by Samuel J. Dwyer III, R. Gilbert Jost, and Roger H. Schneider. SPIE, 1989. http://dx.doi.org/10.1117/12.953301.

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Song, Tzu-An, and Joyita Dutta. "Noise2Void Denoising of PET Images." In 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE, 2020. http://dx.doi.org/10.1109/nss/mic42677.2020.9507875.

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"Image Segmentation Guidance using Pet Information on CT Images in PET/CT Dual Modality." In 2nd International Workshop on Medical Image Analysis and Description for Diagnosis Systems. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003302700750081.

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Thielemans, Kris, Evren Asma, Ravindra M. Manjeshwar, Alex Ganin, and Terence J. Spinks. "Image-based correction for mismatched attenuation in PET images." In 2008 IEEE Nuclear Science Symposium and Medical Imaging conference (2008 NSS/MIC). IEEE, 2008. http://dx.doi.org/10.1109/nssmic.2008.4774427.

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Arabi, Hossein, and Habib Zaidi. "Multiple PET Reconstruction Assisted Non-local Mean Denoising of PET Images." In 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE, 2020. http://dx.doi.org/10.1109/nss/mic42677.2020.9507772.

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Grant, Alexander M., Brian J. Lee, Chen-Ming Chang, and Craig S. Levin. "Simultaneous PET/MRI images acquired with an RF-transmissive PET insert." In 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE, 2014. http://dx.doi.org/10.1109/nssmic.2014.7431007.

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Grant, Alexander M., Brian J. Lee, Chen-Ming Chang, and Craig S. Levin. "Simultaneous PET/MR images acquired with an RF-penetrable PET insert." In 2015 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE, 2015. http://dx.doi.org/10.1109/nssmic.2015.7582026.

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Dutta, Kaushik, Ziping Liu, Richard Laforest, Abhinav Jha, and Kooresh I. Shoghi. "Deep learning framework to synthesize high-count preclinical PET images from low-count preclinical PET images." In Physics of Medical Imaging, edited by Wei Zhao and Lifeng Yu. SPIE, 2022. http://dx.doi.org/10.1117/12.2612729.

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Rota Kops, Elena, and Hans Herzog. "Alternative methods for attenuation correction for PET images in MR-PET scanners." In 2007 IEEE Nuclear Science Symposium Conference Record. IEEE, 2007. http://dx.doi.org/10.1109/nssmic.2007.4437073.

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Lemmens, Catherine, and Johan Nuyts. "Metals in PET/CT: Causes and reduction of artifacts in PET images." In 2008 IEEE Nuclear Science Symposium and Medical Imaging conference (2008 NSS/MIC). IEEE, 2008. http://dx.doi.org/10.1109/nssmic.2008.4774204.

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Reports on the topic "Images PET":

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FDG-PET/CT SUV for Response to Cancer Therapy, Clinically Feasible Profile. Chair Nathan Hall and Jeffrey Yap. Radiological Society of North America (RSNA) / Quantitative Imaging Biomarkers Alliance (QIBA), June 2023. http://dx.doi.org/10.1148/qiba/20230615.

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This QIBA Profile documents specifications and requirements to provide comparability and consistency for quantitative FDG-PET across scanners in oncology. It can be applied to both clinical trial use as well as individual patient management. This document organizes acquisition, reconstruction and post-processing, analysis and interpretation as steps in a pipeline that transforms data to information to knowledge. The document, developed through the efforts of the QIBA FDG-PET Biomarker Committee, has shared content with the FDG-PET UPICT protocol, as well as additional material focused on the devices used to acquire and analyze the FDG-PET data. The QIBA acquisition protocol is largely derived from the FDG-PET UPICT protocol for FDG-PET imaging in clinical trials. In the UPICT protocol, there is a carefully developed hierarchy with tiered levels of protocol compliance. This reflects the recognition that there are valid reasons to perform trials using different levels of rigor, even for the same disease/intervention combination. For example, a high level of image measurement precision may be needed in small, early-phase trials whereas a less rigorous level of precision may be acceptable in large, late-phase trials of the same drug in the same disease setting. This Profile defines the behavioral performance levels and quality control specifications for whole-body FDG-PET/CT scans used in single- and multi-center clinical trials of oncologic therapies. While the emphasis is on clinical trials, this process is also intended to apply for clinical practice. The specific claims for accuracy are detailed in the Claims section. A motivation for the development of this Profile is that while a typical PET/CT scanner measurement system (including all supporting devices) may be stable over days or weeks, this stability cannot be expected over the time that it takes to complete a clinical trial. In addition, there are well known differences between scanners and or the operation of the same type of scanner at different imaging sites. The intended audiences of this document include: Technical staff of software and device manufacturers who create products for this purpose Biopharmaceutical companies, oncologists, and clinical trial scientists designing trials with imaging endpoints Clinical research professionals Radiologists, nuclear medicine physicists, technologists, physicists and administrators at healthcare institutions (1) considering specifications for procuring new PET/CT equipment, (2) designing PET/CT acquisition protocols, (3) making quantitative measurements from PET/CT images Regulators, nuclear medicine physicians, oncologists, and others making decisions based on quantitative image measurements
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Gil Benítez, Alejandro, and María Pascual Mora. LA TOMOGRAFÍA POR EMISIÓN DE POSITRONES (PET); FUNDAMENTOS, DESARROLLO Y APLICACIONES. Fundación Avanza, May 2024. http://dx.doi.org/10.60096/fundacionavanza/2322024.

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El desarrollo e implementación de la tomografía por emisión de positrones (PET) ha supuesto una revolución en el mundo de las técnicas de imagen clínica permitiendo obtener una nueva clase de información.
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Kaufeld, Kimberly, James Wendelberger, and Elizabeth Kelly. Montage (stitched 20X images) Pit Assessment of FY16 DE05. Office of Scientific and Technical Information (OSTI), February 2021. http://dx.doi.org/10.2172/1766986.

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Alhasan, Ahmad, Brian Moon, Doug Steele, Hyung Lee, and Abu Sufian. Chip Seal Quality Assurance Using Percent Embedment. Illinois Center for Transportation, December 2023. http://dx.doi.org/10.36501/0197-9191/23-029.

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This study investigates the use of macrotexture as an indicator of the percent embedment (PE) of aggregate in a chip seal and ultimately, as a quality assurance tool for chip seals. The study included an extensive field- and controlled-testing program from 24 chip seal sections constructed in Illinois. Surface texture measurements were acquired using a high-speed texture profiler and a stationary laser texture device. The analysis showed that stationary texture measurements were more consistent and reliable for estimating PE and characterizing chip seals in the field. Moreover, the ground truth PE values were estimated using an image analysis algorithm implemented on side-view images of cores extracted in the field. The ground truth PE values were estimated using four approaches: the average elevation method, percent embedment of each aggregate method, the peak method, and the aggregate circumference method. The analysis showed that the correlations between the different PE estimation methods are relatively weak, indicating the various methods provide different information and may relate to different characteristics. The general regression models for PE values estimated using the average elevation method and the mean profile depth (MPD) acquired using laser texture scans and the average least dimension (ALD) yielded the highest R2 value of 0.50. The model showed a consistent decreasing trend between PE and MPD estimated using laser texture scans and side-view images. Moreover, the model matched the expected behavior that PE should reach 100% as MPD reaches 0. Finally, four models were recommended correlating PE estimated using the average elevation and each aggregate methods to the MPD (mm) estimated from laser texture scans and ALD (mm) estimated from side-view images.
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Tao, Yang, Amos Mizrach, Victor Alchanatis, Nachshon Shamir, and Tom Porter. Automated imaging broiler chicksexing for gender-specific and efficient production. United States Department of Agriculture, December 2014. http://dx.doi.org/10.32747/2014.7594391.bard.

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Extending the previous two years of research results (Mizarch, et al, 2012, Tao, 2011, 2012), the third year’s efforts in both Maryland and Israel were directed towards the engineering of the system. The activities included the robust chick handling and its conveyor system development, optical system improvement, online dynamic motion imaging of chicks, multi-image sequence optimal feather extraction and detection, and pattern recognition. Mechanical System Engineering The third model of the mechanical chick handling system with high-speed imaging system was built as shown in Fig. 1. This system has the improved chick holding cups and motion mechanisms that enable chicks to open wings through the view section. The mechanical system has achieved the speed of 4 chicks per second which exceeds the design specs of 3 chicks per second. In the center of the conveyor, a high-speed camera with UV sensitive optical system, shown in Fig.2, was installed that captures chick images at multiple frames (45 images and system selectable) when the chick passing through the view area. Through intensive discussions and efforts, the PIs of Maryland and ARO have created the protocol of joint hardware and software that uses sequential images of chick in its fall motion to capture opening wings and extract the optimal opening positions. This approached enables the reliable feather feature extraction in dynamic motion and pattern recognition. Improving of Chick Wing Deployment The mechanical system for chick conveying and especially the section that cause chicks to deploy their wings wide open under the fast video camera and the UV light was investigated along the third study year. As a natural behavior, chicks tend to deploy their wings as a mean of balancing their body when a sudden change in the vertical movement was applied. In the latest two years, this was achieved by causing the chicks to move in a free fall, in the earth gravity (g) along short vertical distance. The chicks have always tended to deploy their wing but not always in wide horizontal open situation. Such position is requested in order to get successful image under the video camera. Besides, the cells with checks bumped suddenly at the end of the free falling path. That caused the chicks legs to collapse inside the cells and the image of wing become bluer. For improving the movement and preventing the chick legs from collapsing, a slowing down mechanism was design and tested. This was done by installing of plastic block, that was printed in a predesign variable slope (Fig. 3) at the end of the path of falling cells (Fig.4). The cells are moving down in variable velocity according the block slope and achieve zero velocity at the end of the path. The slop was design in a way that the deacceleration become 0.8g instead the free fall gravity (g) without presence of the block. The tests showed better deployment and wider chick's wing opening as well as better balance along the movement. Design of additional sizes of block slops is under investigation. Slops that create accelerations of 0.7g, 0.9g, and variable accelerations are designed for improving movement path and images.
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Kenes, Bulent. Per Jimmie Åkesson: A Smiling Wolf in Sheep’s Clothing? European Center for Populism Studies (ECPS), August 2020. http://dx.doi.org/10.55271/lp0002.

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Jimmie Åkesson and his party, the Sweden Democrats (SD), are not yet authentically democratic. They are still “the same old iron gang as usual” despite concerted efforts to change their image. Of course, Åkesson has steered the SD away from the Nazi movement onto a more parliamentary path. But its essence – alarmist resistance to immigrants and Islamophobia – has remained the same, and there is still no solid indication that Åkesson has matured or moderated over the years.
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Tang, H., Ed X. Wu, D. Gallagher, and S. B. Heymsfield. Monochrome Image Presentation and Segmentation Based on the Pseudo-Color and PCT Transformations. Fort Belvoir, VA: Defense Technical Information Center, October 2001. http://dx.doi.org/10.21236/ada412412.

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Kurdziel, Karen, Michael Hagan, Jeffrey Williamson, Donna McClish, Panos Fatouros, Jerry Hirsch, Rhonda Hoyle, Kristin Schmidt, Dorin Tudor, and Jie Liu. Multimodality Image-Guided HDR/IMRT in Prostate Cancer: Combined Molecular Targeting Using Nanoparticle MR, 3D MRSI, and 11C Acetate PET Imaging. Fort Belvoir, VA: Defense Technical Information Center, August 2005. http://dx.doi.org/10.21236/ada446542.

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Piert, Morand. Parametric PET/MR Fusion Imaging to Differentiate Aggressive from Indolent Primary Prostate Cancer with Application for Image-Guided Prostate Cancer Biopsies. Fort Belvoir, VA: Defense Technical Information Center, October 2014. http://dx.doi.org/10.21236/ada612753.

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Piert, Morand. Parametric PET/MR Fusion Imaging to Differentiate Aggressive from Indolent Primary Prostate Cancer with Application for Image-Guided Prostate Cancer Biopsies. Fort Belvoir, VA: Defense Technical Information Center, October 2013. http://dx.doi.org/10.21236/ada598223.

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