Teses / dissertações sobre o tema "Ultrasound image segmentation"
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Gong, Lixin. "Prostate ultrasound image segmentation and registration /". Thesis, Connect to this title online; UW restricted, 2003. http://hdl.handle.net/1773/5937.
Texto completo da fonteRohlén, Robin. "Segmentation of motor units in ultrasound image sequences". Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-126896.
Texto completo da fonteBadiei, Sara. "Prostate segmentation in ultrasound images using image warping and ellipsoid fitting". Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/31737.
Texto completo da fonteApplied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
Quartararo, John David. "Semi-Automated Segmentation of 3D Medical Ultrasound Images". Digital WPI, 2009. https://digitalcommons.wpi.edu/etd-theses/155.
Texto completo da fonteGhose, Soumya. "Robust image segmentation applied to magnetic resonance and ultrasound images of the prostate". Doctoral thesis, Universitat de Girona, 2012. http://hdl.handle.net/10803/98524.
Texto completo da fonteLa segmentació de la pròstata en imatge d'ultrasò (US) i de ressonància magnètica (MRI) permet l'estimació del volum, el registre multi-modal i la planificació quirúrgica de biòpsies guiades per imatge. L'objectiu d'aquesta tesi és el desenvolupament d'algorismes automàtics per a la segmentació de la pròstata en aquestes modalitats. Es proposa un aprenentatge automàtic inical per obtenir una primera classificació de la pròstata que permet, a continuació, la inicialització i evolució de diferents models deformables. Per imatges d'US, es proposen un model explícit basat en forma i informació regional i un model implícit basat en la minimització d'una funció d'energia. En MRI, les probalitats inicials es fusionen amb una imatge de probabilitat provinent d'una segmentació basada en atlas, i la minimització es realitza mitjançant tècniques de grafs. El resultat final és una significant millora dels algorismes actuals en ambdues modalitats d'imatge.
Wen, Shuangyue. "Automatic Tongue Contour Segmentation using Deep Learning". Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38343.
Texto completo da fonteZhao, Ningning. "Inverse problems in medical ultrasound images - applications to image deconvolution, segmentation and super-resolution". Phd thesis, Toulouse, INPT, 2016. http://oatao.univ-toulouse.fr/16613/1/Zhao.pdf.
Texto completo da fontevon, Lavante Etienne. "Segmentation and sizing of breast cancer masses with ultrasound elasticity imaging". Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:81225f61-6b83-405b-aed5-17b316ed586a.
Texto completo da fonteRackham, Thomas. "Ultrasound segmentation tools and their application to assess fetal nutritional health". Thesis, University of Oxford, 2016. http://ora.ox.ac.uk/objects/uuid:5d102b18-dd32-4004-8aa5-b04242139daa.
Texto completo da fonteNavarrete, Hurtado Hugo Ariel. "Electromagnetic models for ultrasound image processing". Doctoral thesis, Universitat Politècnica de Catalunya, 2016. http://hdl.handle.net/10803/398235.
Texto completo da fonteEl ruido Speckle aparece cuando se utilizan sistemas de iluminación coherente, como por ejemplo Láser, Radar de Apertura Sintética (SAR), Sonar, Resonancia Magnética, rayos X y ultrasonidos. Los ecos dispersados por los centros dispersores distribuidos al azar en la estructura microscópica del medio son el origen de este fenómeno, que caracteriza las imágenes coherentes con un aspecto granular. Se puede demostrar que el ruido Speckle es de carácter multiplicativo, fuertemente correlacionados y lo más importante, con estadística no Gaussiana. Estas características son muy diferentes de la suposición tradicional de ruido aditivo gaussiano blanco, a menudo asumida en la segmentación de imágenes, filtrado, y en general, en el procesamiento de imágenes; lo cual se traduce en la reducción de la eficacia de los métodos para la extracción de información de la imagen final. La modelización estadística es de particular relevancia cuando se trata con datos Speckle, a fin de obtener algoritmos de procesamiento de imágenes eficientes. Además, el procesamiento no lineal de señales empleado en sistemas clínicos de imágenes por ultrasonido para reducir el rango dinámico de la señal de eco de entrada de manera que coincida con el rango dinámico más pequeño del dispositivo de visualización y resaltar así los objetos con dispersión más débil, modifica radicalmente la estadística de los datos. Esta reducción en el rango dinámico se logra normalmente a través de un amplificador logarítmico es decir, la compresión logarítmica, que comprime selectivamente las señales de entrada y una forma analítica para la expresión de la función de densidad de los datos transformados logarítmicamente es por lo general difícil de derivar. Esta tesis se centra en las distribuciones estadísticas de la amplitud de la señal comprimida logarítmicamente en las imágenes coherentes, y su principal objetivo es el desarrollo de un modelo estadístico general para las imágenes por ultrasonido comprimidas logarítmicamente en modo-B. El modelo desarrollado se adaptó, realizando las analogías físicas relevantes, del modelo multiplicativo en radares de apertura sintética (SAR). El Modelo propuesto puede describir correctamente los datos comprimidos logarítmicamente a partir datos generados con los diferentes modelos propuestos en la literatura especializada en procesamiento de imágenes por ultrasonido. Además, el modelo se aplica con éxito para modelar ecocardiografías en vivo. Se enuncian y demuestran los teoremas necesarios para dar cuenta de una demostración matemática rigurosa de la validez y generalidad del modelo. Además, se da una interpretación física de los parámetros y se establecen las conexiones entre el teorema central del límite generalizado, el modelo multiplicativo y la composición de distribuciones para los diferentes modelos propuestos hasta a la fecha. Se demuestra además que los parámetros del amplificador logarítmico se incluyen dentro de los parámetros del modelo y se estiman usando los métodos estándar de momentos y máxima verosimilitud. Por último, tres aplicaciones se desarrollan: filtrado de ruido Speckle, segmentación de ecocardiografías y un nuevo enfoque para la evaluación de la fracción de eyección cardiaca.
Hammer, Steven James. "Engineering a 3D ultrasound system for image-guided vascular modelling". Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/4253.
Texto completo da fonteAbuAzzah, Ezzat. "A 4D ultrasound imaging automation platform for modelling and assessment of ultrasound target dynamics using direct visual servoing and machine learning". Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/134613/1/Ezzat_AbuAzzah_Thesis.pdf.
Texto completo da fonteChiu, Bernard. "A new segmentation algorithm for prostate boundary detection in 2D ultrasound images". Thesis, Waterloo, Ont. : University of Waterloo, [Dept. of Electrical and Computer Engineering], 2003. http://etd.uwaterloo.ca/etd/bcychiu2003.pdf.
Texto completo da fonte"A thesis presented to the University of Waterloo in fulfilment of the thesis requirement for the degree of Master of Applied Science in Electrical and Computer Engineering". Includes bibliographical references.
Yaqub, Mohammad. "Automatic measurements of femoral characteristics using 3D ultrasound images in utero". Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:857a12d2-ffe3-4fa6-89c3-0d8319ee2fbb.
Texto completo da fonteStebbing, Richard. "Model-based segmentation methods for analysis of 2D and 3D ultrasound images and sequences". Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:f0e855ca-5ed9-4e40-994c-9b470d5594bf.
Texto completo da fonteSun, Shanhui. "Automated and interactive approaches for optimal surface finding based segmentation of medical image data". Diss., University of Iowa, 2012. https://ir.uiowa.edu/etd/3543.
Texto completo da fonteKasimoglu, Ismail Hakki. "Estimation of a Coronary Vessel Wall Deformation with High-Frequency Ultrasound Elastography". Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19762.
Texto completo da fonteMozaffari, Maaref Mohammad Hamed. "A Real-Time and Automatic Ultrasound-Enhanced Multimodal Second Language Training System: A Deep Learning Approach". Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40477.
Texto completo da fonteEklund, Anders, Paul Dufort, Daniel Forsberg e Stephen LaConte. "Medical Image Processing on the GPU : Past, Present and Future". Linköpings universitet, Medicinsk informatik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93673.
Texto completo da fontePrevost, Raphaël. "Méthodes variationnelles pour la segmentation d'images à partir de modèles : applications en imagerie médicale". Phd thesis, Université Paris Dauphine - Paris IX, 2013. http://tel.archives-ouvertes.fr/tel-00932995.
Texto completo da fonteLeclerc, Sarah Marie-Solveig. "Automatisation de la segmentation sémantique de structures cardiaques en imagerie ultrasonore par apprentissage supervisé". Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEI121.
Texto completo da fonteThe analysis of medical images plays a critical role in cardiology. Ultrasound imaging, as a real-time, low cost and bed side applicable modality, is nowadays the most commonly used image modality to monitor patient status and perform clinical cardiac diagnosis. However, the semantic segmentation (i.e the accurate delineation and identification) of heart structures is a difficult task due to the low quality of ultrasound images, characterized in particular by the lack of clear boundaries. To compensate for missing information, the best performing methods before this thesis relied on the integration of prior information on cardiac shape or motion, which in turns reduced the adaptability of the corresponding methods. Furthermore, such approaches require man- ual identifications of key points to be adapted to a given image, which makes the full process difficult to reproduce. In this thesis, we propose several original fully-automatic algorithms for the semantic segmentation of echocardiographic images based on supervised learning ap- proaches, where the resolution of the problem is automatically set up using data previously analyzed by trained cardiologists. From the design of a dedicated dataset and evaluation platform, we prove in this project the clinical applicability of fully-automatic supervised learning methods, in particular deep learning methods, as well as the possibility to improve the robustness by incorporating in the full process the prior automatic detection of regions of interest
Li, Yingping. "Artificial intelligence and radiomics in cancer diagnosis". Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG053.
Texto completo da fonteArtificial intelligence (AI) has been widely used in the research field of AI-assisted diagnosis, treatment, and personalized medicine. This manuscript focuses on the application of artificial intelligence methods including deep learning and radiomics in cancer diagnosis. First, effective image segmentation is essential for cancer diagnosis and further radiomics-based analysis. We proposed a new approach for automatic lesion segmentation in ultrasound images, based on a multicentric and multipathology dataset displaying different types of cancers. By introducing the group convolution, we proposed a lightweight U-net network without sacrificing the segmentation performance. Second, we processed the clinical Magnetic Resonance Imaging (MRI) images to noninvasively predict the glioma subtype as defined by the tumor grade, isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status. We proposed a radiomics-based approach. The prediction performance improved significantly by tuning different settings in the radiomics pipeline. The characteristics of the radiomic features that best distinguish the glioma subtypes were also analyzed. This work not only provided a radiomics pipeline that works well for predicting the glioma subtype, but it also contributed to the model development and interpretability. Third, we tackled the challenge of reproducibility in radiomics methods. We investigated the impact of different image preprocessing methods and harmonization methods (including intensity normalization and ComBat harmonization) on the radiomic feature reproducibility in MRI radiomics. The conclusion showed that ComBat method is essential to remove the nonbiological variation caused by different image acquisition settings (namely, scanner effects) and improve the feature reproducibility in radiomics studies. Meanwhile, intensity normalization is also recommended because it leads to more comparable MRI images and more robust harmonization results. Finally, we investigated improving the ComBat harmonization method by changing its assumption to a very common case that scanner effects are different for different classes (like tumors and normal tissues). Although the proposed model yielded disappointing results, surely due to the lack of enough proper constraints to help identify the parameters, it still paved the way for the development of new harmonization methods
Cohen, Emmanuel. "Cartographie, analyse et reconnaissance de réseaux vasculaires par Doppler ultrasensible 4D". Thesis, Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLED046/document.
Texto completo da fonteUltrasensitive Doppler is a new ultrasound imaging technique allowing the observation of blood flows with a very fine resolution and no contrast agent. Applied to cerebral microvascular imaging in rodents, this method produces very fine vascular 3D maps of the brain at high spatial resolution. These vascular networks contain characteristic tubular structures that could be used as landmarks to localize the position of the ultrasonic probe and take advantage of the easy-to-use properties of ultrasound devices such as low cost and portability. Thus, we developed a first neuronavigation system in rodents based on automatic registration of brain images. Using minimal path extraction methods, we developed a new isotropic segmentation framework for 3D geometric analysis of vascular networks (extraction of centrelines, diameters, curvatures, bifurcations). This framework was applied to quantify brain and tumor vascular networks, and finally leads to the development of point cloud registration algorithms for temporal monitoring of tumors
Quartararo, John David. "Semi-automated segmentation of 3D medical ultrasound images". Worcester, Mass. : Worcester Polytechnic Institute, 2008. http://www.wpi.edu/Pubs/ETD/Available/etd-020509-161314/.
Texto completo da fonteKeywords: 3d ultrasound; ultrasound; image processing; image segmentation; 3d image segmentation; medical imaging Includes bibliographical references (p.142-148).
Chalana, Vikram. "Deformable models for segmentation of medical ultrasound images /". Thesis, Connect to this title online; UW restricted, 1996. http://hdl.handle.net/1773/8025.
Texto completo da fonteGjedrem, Stian Dalene, e Gunn Marie Navestad. "Segmentation of Neuro Tumours : from MR and Ultrasound images". Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2005. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9195.
Texto completo da fonteWe have implemented and tested segmentation methods for segmenting brain tumours from magnetic resonance (MR) and ultrasound data. Our work in this thesis mainly focuses on active contours, both parametric (snakes) and geometric contours (level set). Active contours have the advantage over simpler segmentation methods that they are able to take both high- and low-level information into consideration. This means that the result they produce both depends on shape as well as intensity information from the input image. Our work is based on the results from an earlier completed depth study which investigated different segmentation methods. We have implemented and tested one simplified gradient vector flow snake model and four level set approaches: fast marching level set, geodesic level set, canny edge level set, and Laplacian level set. The methods are evaluated based on precision of the region boundary, sensitivity to noise, the effort needed to adjust parameters and the time to perform the segmentation. We have also compared the results with the result from a region growing method. We achieved promising results for active contour segmentation methods compared with other, simpler segmentation methods. The simplified snake model has given promising results, but has to be subject to more testing. Furthermore, tests with four variants of the level set method have given good results in most cases with MR data and in some cases with ultrasound data.
Shan, Juan. "A Fully Automatic Segmentation Method for Breast Ultrasound Images". DigitalCommons@USU, 2011. https://digitalcommons.usu.edu/etd/905.
Texto completo da fonteMattsson, Per, e Andreas Eriksson. "Segmentation of Carotid Arteries from 3D and 4D Ultrasound Images". Thesis, Linköping University, Department of Electrical Engineering, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1141.
Texto completo da fonteThis thesis presents a 3D semi-automatic segmentation technique for extracting the lumen surface of the Carotid arteries including the bifurcation from 3D and 4D ultrasound examinations.
Ultrasound images are inherently noisy. Therefore, to aid the inspection of the acquired data an adaptive edge preserving filtering technique is used to reduce the general high noise level. The segmentation process starts with edge detection with a recursive and separable 3D Monga-Deriche-Canny operator. To reduce the computation time needed for the segmentation process, a seeded region growing technique is used to make an initial model of the artery. The final segmentation is based on the inflatable balloon model, which deforms the initial model to fit the ultrasound data. The balloon model is implemented with the finite element method.
The segmentation technique produces 3D models that are intended as pre-planning tools for surgeons. The results from a healthy person are satisfactory and the results from a patient with stenosis seem rather promising. A novel 4D model of wall motion of the Carotid vessels has also been obtained. From this model, 3D compliance measures can easily be obtained.
Chiu, Edwin. "Lossy compression of medical ultrasound images using space-frequency segmentation". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0027/MQ51315.pdf.
Texto completo da fonteMuzzolini, Russell E. "A volumetric approach to segmentation and texture characterisation of ultrasound images". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq24041.pdf.
Texto completo da fonteAnxionnat, Adrien. "Segmentation of high frequency 3D ultrasound images for skin disease characterization". Thesis, KTH, Teknisk informationsvetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-209203.
Texto completo da fonteDetta arbete är grundat i en dermatologs behov att undersöka hudens egenskaperpå djupet. Påverkan av hudsjukdomar så som acne på dermala vävanderär fortfarande svårt att bedöma. Bland möjligheterna är högfrekvent ultraljudsavbildningett paradigmskifte för undersökning och karakterisering av övre ochdjupa dermis. I detta syfte har en kohort av 58 högfrekventa 3D bilder förvärvatsav det Franska laboratoriet Pierre Fabre för att studera sjukdomen acne vulgaris.Denna vanliga hudsjukdom är en utmaning för samhället och en bördasom påverkar de i slutet av tonåren över hela världen. Protokollet utvecklatav Pierre Fabre innebar att undersöka en lesion varje dag över 9 dagar förolika patienter med ultraljudavbildning. Den insamlade datan visar hudens epidermisoch dermis struktur med en fantastiskt hög upplösning. Strategin vianvände för att studera denna data kan förklaras i tre steg. För det första,hittas epidermis yta bland artifakter och brus tack vare en robust level-set algoritm.För det andra, acne äckar hittas på höjdkartan och associeras tillvarandra bland mätdatan genom en tröskeljämförelse över lokala variationer.Även potentiellt inammatoriska dermala hålrum relaterade till varje lesion blirgeometriskt ochj statistiskt kännetecknade för att bedöma sjukdomens förlopp.Resultaten framför en automatisk algoritm som gör det möjligt för dermatologeratt undersöka acne vulgaris lesioner och utmärka de i ett dataset. Detta kandärmed vara en kraftfull verktygslåda för att undersöka inverkan av en behandlingtill denna sjukdom.
Pathak, Sayan Dev. "Computer-aided segmentation of anatomical features in transrectal ultrasound prostate images /". Thesis, Connect to this title online; UW restricted, 2000. http://hdl.handle.net/1773/8125.
Texto completo da fonteMarcomini, Karem Daiane. "Caracterização de lesões em imagens digitais de ultrassonografia e elastografia da mama utilizando técnicas inteligentes". Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/18/18152/tde-08122017-113952/.
Texto completo da fonteMany procedures have been developed to aid in the early detection and diagnosis of breast cancer. In this context, Computer-Aided Diagnosis (CADx) systems were designed to provide to the specialist a reliable second opinion. This study presents the proposal of investigating the diagnostic ability of a computational system in the characterization of suspicious findings in B-mode ultrasound and breast elastography imaging. The database consisted of 31 malignant and 52 benign lesions and an additional data set containing 206 lesions (144 benign and 62 malignant) seen only on the B-mode ultrasound for performing the machine learning tests. Three radiologists drew manually the contour of the lesions in B-mode ultrasound and we used an automatic technique to segment the lesions. Then, the contour was mapped in the elastography image. The lesions were classified using the CADx system developed for B-mode ultrasound and strain elastography. We calculated the sensitivity, specificity and AUC to evaluate the data. The developed CADx system provided a diagnostic concordance in the classification of breast lesions from the different ways of contour determination (manual and automatic), allowing to reduce the diagnostic variability. In addition, the CADx system showed superior results to the visual analysis of the radiologist. When the radiologist associated both examinations (B-mode ultrasound and elastography), his visual analysis provided 87.10%, 55.77% and 0.714 of sensitivity, specificity and AUC, respectively. When we considered the result provided by the association between B-mode ultrasound and elastography images, the CADx system provided a comparative increase of about 7% of sensitivity and 17.2% of specificity, using the contour delimited by the most experienced radiologist. In addition, a positive influence was observed in the use of the computational tool by radiologists, since, on average, their sensitivity and specificity indexes also increased in relation to the conventional analysis, from 87.1% and 55.8% to 90.3% and 73.1%, respectively.
Zahnd, Guillaume. "Estimation du mouvement bi-dimensionnel de la paroi artérielle en imagerie ultrasonore par une approche conjointe de segmentation et de speckle tracking". Phd thesis, INSA de Lyon, 2012. http://tel.archives-ouvertes.fr/tel-00835828.
Texto completo da fonteGarnier, Carole. "Segmentation de la prostate pour la thérapie par Ultrasons Haute Intensité guidée par l'image". Phd thesis, Université Rennes 1, 2009. http://tel.archives-ouvertes.fr/tel-00498035.
Texto completo da fonteMassich, i. Vall Joan. "Deformable object segmentation in ultra-sound images". Doctoral thesis, Universitat de Girona, 2013. http://hdl.handle.net/10803/128329.
Texto completo da fonteEn aquest treball, es proposa un sistema automàtic per generar delineacions acurades de lesions de mama en imatges d’ultrasò. El sistema proposat planteja el problema de trobar la delineació corresponent a la minimització d’un sistema probabilístic multiclasse mitjançant el tall de mínim cost del graf que representa la imatge. El sistema representa la imatge com un conjunt de regions i infereix una classe per cada una d’aquestes regions a partir d’uns models estadístics obtinguts d’unes imatges d’entrenament. El principal avantatge del sistema és que divideix la tasca en subtasques més fàcils d’adreçar i després soluciona el problema de forma global
Zhao, Fangwei. "Multiresolution analysis of ultrasound images of the prostate". University of Western Australia. School of Electrical, Electronic and Computer Engineering, 2004. http://theses.library.uwa.edu.au/adt-WU2004.0028.
Texto completo da fonteProvent, Pierre. "Segmentation d'images par analyse statistique de textures : application aux images échocardiographiques". Paris 12, 1991. http://www.theses.fr/1991PA120049.
Texto completo da fonteSelagamsetty, Srinivasa Siddhartha. "Exploring a Methodology for Segmenting Biomedical Images using Deep Learning". University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1573812579683504.
Texto completo da fonteSandoval, Niño Zulma. "Planning and guidance of ultrasound guided High Intensity Focused Ultrasound cardiac arrhythmia therapy". Thesis, Rennes 1, 2015. http://www.theses.fr/2015REN1S044/document.
Texto completo da fonteThe work presented in this document aims at developing new image-processing methods to improve the planning and guidance of transesophageal HIFU atrial fibrillation therapy. This document is divided into two parts, namely therapy planning and therapy guidance. We first propose novel therapy planning methods that exploit high-resolution pre-operative CT or MRI information to extract patient-specific anatomical details and to define future therapeutic procedures. Our specific methodological contributions concern the following: an automatically-refined atlas-based segmentation approach to extract the left atrium and pulmonary veins; the delineation of the lesion lines on the original or segmented volume; and the reconstruction of a volume adapted to future intraoperative transesophageal navigation. Secondly, our proposal of a novel registration approach for use in therapy guidance aligns intraoperative 2D ultrasound with preoperative 3D CT information. This approach first carries out a systematic statistical evaluation to select the best similarity measure for our application and then takes advantage of the geometrical constraints of the transesophageal HIFU probe to simplify the registration process. Our proposed methods have been evaluated on digital and/or physical phantoms and on real clinical data
Mohamed, Samar. "Integrated Feature Analysis for Prostate Tissue Characterization Using TRUS Images". Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/2888.
Texto completo da fonteComputer Aided Diagnosis (CAD) was introduced to help in the diagnosis in order to assist in the biopsy operations. Usually, CAD is carried out utilizing either the clinical data, using data mining techniques, or using features extracted from either TransRectal UltraSound (TRUS) images or the Radio Frequency (RF) signals.
The challenge is that TRUS images' quality is usually poor compared to either Magnetic Resonance Imaging (MRI) or the Computed Tomography (CT). On the other hand, ultrasound imaging is more convenient because of its simple instrumentation and mobility capability compared to either CT or MRI. Moreover, TRUS is far less expensive and does not need certain settings compared to either MRI or CT. Accordingly; the main motivation of this research is to enhance the outcome of TRUS images by extracting as much information as possible from it. The main objective of this research is to implement a powerful noninvasive CAD tool that integrates all the possible information gathered from the TRUS images in order to mimic the expert radiologist opinion and even go beyond his visual system capabilities, a process that will in turn assist the biopsy operation. In this sense, looking deep in the TRUS images by getting some mathematical measures that characterize the image and are not visible by the radiologist is required to achieve the task of cancer recognition.
This thesis presents several comprehensive algorithms for integrated feature analysis systems for the purpose of prostate tissue classification. The proposed algorithm is composed of several stages, which are: First, the regions that are highly suspicious are selected using the proposed Gabor filter based ROI identification algorithm.
Second, the selected regions are further examined by constructing different novel as well as typical feature sets. The novel constructed feature sets are composed of statistical feature sets, spectral feature sets and model based feature sets.
Next, the constructed features were further analyzed by selecting the best feature subset that identifies the cancereus regions. This task is achieved by proposing different dimensionality reduction methods which can be categorized into: Classifier dependent feature selection (Mutual Information based feature selection), classifier independent feature selection, which is based mainly on tailoring the Artificial life optimization techniques to fit the feature selection problem and Feature Extraction, which transforms the data to a new lower dimension space without any degradation in the information and with no correlation among the transformed lower dimensional features.
Finally, the last proposed fragment in this thesis is the Spectral Clustering algorithm, which is applied to the TRUS images. Spectral Clustering is a novel fast algorithm that can be used in order to obtain a fast initial estimate of the cancer regions. Moreover, it can be used to support the decision obtained by the proposed cancer recognition algorithm. This decision support process is crucial at this stage as the gold standards used in obtaining the results shown in this thesis is mainly the radiologist's markings on the TRUS images. This gold standards is not considered as credible since the radiologist's best accuracy is approximately 65 %.
In conclusion, this thesis introduces different novel complete algorithms for automatic cancerous regions detection in the prostate gland utilizing TRUS images. These proposed algorithms complement each other in which the results obtained using either of the proposed algorithms support each other by resulting in the same classification accuracy, sensitivity and specificity. This result proves the remarkable quality of the constructed features as well as the superiority of the introduced feature selection and feature extraction methods to detect cancerous regions in the prostate gland.
Nguyen, Khac Lan. "Modèles de champ de phase et modèles Lattice Boltzmann pour la segmentation 3D de tumeurs en imagerie ultrasons hautes fréquences". Thesis, La Rochelle, 2019. http://www.theses.fr/2019LAROS011.
Texto completo da fonteIn this thesis, we are interested in the problem of 3D segmentation of skin tumors in high frequency ultrasound images. We focus mainly on two questions: how best to estimate the volume of tumors (in accordance with references produced by dermatologists) and how to produce algorithms whose computation times are close to real time? First, we describe a new model, log-likelihood Cahn-Hilliard (LLCH), based on a variational formulation coupling a data attachment term computed from non-parametric estimates and a regularization term derived from a phase transition dynamic (Allen Cahn reaction diffusion equation). This model is tested with a first multigrid implementation using exact solutions calculated with a Lie splitting. Secondly, we are interested in the possibility of implementing the LLCH model using lattice Boltzmann methods (LBM). The underlying dynamic is not physical in nature, so this implementation is not direct and is subject to instability problems. We show that, due to the specificities of the data attachment term, the BGK schemes, with simple relaxation time, do not ensure sufficient stability. We then use MRT schemes, with multiple relaxation times, which allow us to gain stability by introducing additional parameters. The adjustment of the so-called quartic parameters makes it possible to obtain fourth-order exact schemes that are numerically stable. Tests performed on a clinical database with ground truth provided by dermatologists show that the results obtained with the two proposed implementations are much better than those obtained with level sets methods and that our model is a good alternative to overcome the problem of underestimation of tumor volume. The computation times, for 3D images of about 70 million voxels, are very short and well adapted for practical use in medical environments
Dahdouh, Sonia. "Filtrage, segmentation et suivi d'images échographiques : applications cliniques". Phd thesis, Université Paris Sud - Paris XI, 2011. http://tel.archives-ouvertes.fr/tel-00647326.
Texto completo da fonteHesko, Branislav. "Aktivní kontury pro segmentaci ultrazvukových dat". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-221388.
Texto completo da fonteFouquet, Clément. "Aide à la détection et à la reconnaissance de défauts structurels dans les pipelines par analyse automatique des images XtraSonic". Thesis, Cergy-Pontoise, 2014. http://www.theses.fr/2014CERG0729/document.
Texto completo da fonteTRAPIL is a French society who is in charge of exploitation and maintenance of oil pipelines. Maintenance of buried pipeline implies the use of ultrasonic sensor-equipped devices, providing thickness and structural maps of the pipe, which are analysed by experts in order to detect and identify defects that may appear or evolve.The objective of this work is to provide an algoritmic solution allowing to accelerate and aid the experts's work with modern image and signal processing methods.Our approach follows the experts's operating mode and is divided in three sections.First, a weld detection is realized allowing to split the pipe in tubes. The signals of probes representing the circumference of the pipe are regrouped and compressed through an abrupt change detection, using short and long-term average comparison, then the resulting signals are merged using a unique weightening function allowing a massive increase of the contrast between welds and noise, offering near-perfect detection and localization.The tubes then undergoes a first segmentation aiming at eliminating a large amount of sane pixels. Using histogram modelization through an EM algorithm tuned specially for our purpose, the algorithm follows a recursive approach comparable to split and merge methods to detect and isolate dangerous areas.Finally, those dangerous areas are identified with a Random Forest, which has been learnt on a large amount of defect examples. This third part is greatly focused on the study of different pattern recognition methods applied on our new problematic.Through those different steps, the solution we brought allows TRAPIL to save a lot of time on the most tedious tasks of the analysis process (for example 30% of gain in processing time for the weld detection) and offers new commercial possibilities, like for example the possibility to provide their clients a first report in a matter of days, while the manual analysis is completed, which can take more than a month
Mora, Cofré Marco. "Ensemble de niveaux robustes au speckle et recalage B-spline : application à la segmentation et l'analyse du mouvement cardiaque par des images ultrasons". Toulouse, INPT, 2008. http://ethesis.inp-toulouse.fr/archive/00000658/.
Texto completo da fonteAnalysing ultrasound images to estimate local motion of heart walls is widely used to diagnose cardiac malformations. Unfortunately, this modality produces images with a high level of speckle, causing erroneous detection of cavities. This thesis presents a method for estimating heart cavity motion in 2D images. We propose a new level set model to segment cardiac ultrasound images. This model is supported by a stopping term adapted to speckle. Instead of the classical gradient, our stopping term is based on the coeficient of variation. Morever, we improved the detection of contours of this function by adding a supervised clasification based on a Multilayer Perceptron. The obtained results show a significant increase of the precision. The motion estimation is done by means of an adaptative registration process consists of three phases. First, we estimate a linear transform using the ICP algorithm to remove the linear difference between the cavities. The second phase consists of calculating a global B-spline transformation. Finally, we perform a Hierarchical B-spline refinement in regions with unsatisfactory deviations. The experimentations show that our model allows a precise deformation of the heart walls
Mora, Cofré Marco Ayache Alain. "Ensemble de niveaux robustes au speckle et recalage B-spline application à la segmentation et l'analyse du mouvement cardiaque par des images ultrasons /". Toulouse : INP Toulouse, 2008. http://ethesis.inp-toulouse.fr/archive/00000658.
Texto completo da fonteEsneault, Simon. "Planning pour la thérapie de tumeur du foie par ultrasons haute intensité". Phd thesis, Université Rennes 1, 2009. http://tel.archives-ouvertes.fr/tel-00497749.
Texto completo da fonteYang, Qing. "Segmentation d'images ultrasonores basée sur des statistiques locales avec une sélection adaptative d'échelles". Phd thesis, Université de Technologie de Compiègne, 2013. http://tel.archives-ouvertes.fr/tel-00869975.
Texto completo da fonteCheng, Jie-Zhi, e 鄭介誌. "Cell-Based Image Segmentation for 2D and 2D Series Ultrasound Images". Thesis, 2007. http://ndltd.ncl.edu.tw/handle/74833813995255310003.
Texto completo da fonte國立臺灣大學
醫學工程學研究所
95
Boundary information of the object of interest in sonography is the fundamental basis for many clinical studies. It can help to manifest the abnormality of anatomy by characterizing the morphological features and plays the essential role in numerous quantitative ultrasound image analyses. For instance, the evaluation of functional properties of heart demands the quantification of the deformation of epi- and endo-cardiac surfaces. To draw a convincing conclusion for the quantitative analysis, the boundary information should be reliable and efficiently generated― which means robust image segmentation techniques are necessary. This study addresses the challenging segmentation problem of ultrasound images into two parts: 2D and 2D series. Theses two parts are attacked by the two proposed algorithms, i.e. ACCOMP and C2RC-MAP algorithms, respectively. The unique feature of the proposed algorithms is the concept of cell-based. The cell is the catchment basin tessellated by two-pass watershed transformation and is served as the basic operational unit in the two proposed algorithms. Taking the cell tessellation as the basis can be beneficial in three main points. First, comparing to directly finding solutions on pixels, searching on cells is more efficient. It is because the search space spanned by cells is dramatically smaller than the space of pixels. Therefore redundant computation could be saved. Second, the concrete region and edge information can be obtained in the cell tessellation. The concrete information in regions and edges could be valuable clues to assist the segmentation task. Third, as the cell is the group of pixels with homogeneous intensity, it might be more robust to noise in statistics— which could potentially improve the task of image process in ultrasound images. With these three advantages, cell-based image segmentation approaches might be more efficacious and efficient than pixel-based approaches. The ACCOMP algorithm is a two-phase data-driven approach, which is constituted by the partition and the edge grouping phases. The partition phase is purposed to tessellate the image or ROI with prominent components and is carries out by the cell competition algorithm. For the second phase, it is realized by the cell-based graph-traversing algorithm. Focusing on the edge information, the complicated echogenicity problem can be bypassed. The ACCOMP algorithm is validated on 300 breast sonograms, including 165 carcinomas and 135 benign cysts. The results show that more than 70% of the derived boundaries fall within the span of the manually outlines under 95% confident interval. The robustness of reproducibility is confirmed by the Friedman test, the p-values of which is 0.54. It has also suggested that the lesions sizes derived by the ACCOMP algorithm are highly correlated with the lesions defined by the average manually delineated boundaries. To ensure the delineated boundaries of a series of 2D images closely following the visually perceivable edges with high boundary coherence between consecutive slices, the C2RC-MAP algorithm is proposed. It deforms the region boundary in a cell-by-cell fashion through a cell-based two-region competition process. The cell-based deformation is guided by a cell-based MAP framework with a posterior function characterizing the distribution of the cell means in each region, the salience and shape complexity of the region boundary and the boundary coherence of the consecutive slices. The C2RC-MAP algorithm has been validated using 10 series of breast sonograms, including 7 compression series and 3 freehand series. The compression series contains 2 carcinoma and 5 fibroadenoma cases and the freehand series 2 carcinoma and 1 fibroadenoma cases. The results show that more than 70% of the derived boundaries fall within the span of the manually delineated boundaries. The robustness of the proposed algorithm to the variation of ROI is confirmed by the Friedman tests, the p-values of which are 0.517 and 0.352 for the compression and freehand series groups, respectively. The Pearson’s correlations between the lesion sizes derived by the proposed algorithm and those defined by the average manually delineated boundaries are all higher than 0.990. The overlapping and difference ratios between the derived boundaries and the average manually delineated boundaries are mostly higher than 0.90 and lower than 0.13, respectively. For both series groups, all assessments conclude that the boundaries derived by the proposed algorithm be comparable to those delineated manually. Moreover, it is shown that the proposed algorithm is superior to the Chan and Vese level set method based on the paired-sample t-tests on the performance indices at 5% significance level.