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Relevant bibliographies by topics / Imaging methodologies

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Academic literature on the topic 'Imaging methodologies'

Author: Grafiati

Published: 19 October 2024

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Journal articles on the topic "Imaging methodologies"

1

Smith, Sarah E., Brian D. Slaughter, and Jay R. Unruh. "Imaging methodologies for systems biology." Cell Adhesion & Migration 8, no. 5 (September 3, 2014): 468–77. http://dx.doi.org/10.4161/cam.29152.

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López, Claudia S., Kevin Loftis, Guillaume Thibault, Sunjong Kwon, Erin Stempinski, Jessica L. Riesterer, and Joe W. Gray. "Correlation Of Imaging Technologies: Methodologies." Microscopy and Microanalysis 25, S2 (August 2019): 2678–79. http://dx.doi.org/10.1017/s1431927619014120.

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Pogue, Brian W., Summer L. Gibbs-Strauss, Pablo A. Valdés, Kimberley S. Samkoe, David W. Roberts, and Keith D. Paulsen. "Review of Neurosurgical Fluorescence Imaging Methodologies." IEEE Journal of Selected Topics in Quantum Electronics 16, no. 3 (2010): 493–505. http://dx.doi.org/10.1109/jstqe.2009.2034541.

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MacDonald, A. B. "Borrelia burgdorferi tissue morphologies and imaging methodologies." European Journal of Clinical Microbiology & Infectious Diseases 32, no. 8 (March 12, 2013): 1077–82. http://dx.doi.org/10.1007/s10096-013-1853-5.

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Pogue, Brian W., Summer Gibbs-Strauss, Pablo A. Valdés, Kimberley Samkoe, David W. Roberts, and Keith D. Paulsen. "Correction to “Review of Neurosurgical Fluorescence Imaging Methodologies”." IEEE Journal of Selected Topics in Quantum Electronics 16, no. 6 (November 2010): 1847. http://dx.doi.org/10.1109/jstqe.2010.2084074.

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Takeda, Mitsuo, Wolfgang Osten, and Eriko Watanabe. "Holographic 3D Imaging through Random Media: Methodologies and Challenges." Light: Advanced Manufacturing 3 (2022): 1. http://dx.doi.org/10.37188/lam.2022.014.

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Magno, Cathryn, and Jackie Kirk. "Imaging girls: visual methodologies and messages for girls' education." Compare: A Journal of Comparative and International Education 38, no. 3 (June 2008): 349–62. http://dx.doi.org/10.1080/03057920802066667.

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Liu, Shu-Lin, Zhi-Gang Wang, Hai-Yan Xie, An-An Liu, Don C. Lamb, and Dai-Wen Pang. "Single-Virus Tracking: From Imaging Methodologies to Virological Applications." Chemical Reviews 120, no. 3 (January 17, 2020): 1936–79. http://dx.doi.org/10.1021/acs.chemrev.9b00692.

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Smith, Louise E., Rod Smallwood, and Sheila Macneil. "A comparison of imaging methodologies for 3D tissue engineering." Microscopy Research and Technique 73, no. 12 (October 27, 2010): 1123–33. http://dx.doi.org/10.1002/jemt.20859.

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Li, Gan, Michael S. Westphall, Austin Z. Salome, Kenneth W. Lee, Joshua J. Coon, and Timothy Grant. "New methodologies for preparing and imaging cryo-EM samples." Acta Crystallographica Section A Foundations and Advances 79, a1 (July 7, 2023): a159. http://dx.doi.org/10.1107/s2053273323098406.

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Dissertations / Theses on the topic "Imaging methodologies"

1

Czapla-Myers, Jeffrey S. "Spectral response function characterization methodologies for imaging spectrometers." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/MQ56168.pdf.

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Giacometti, A. "Evaluating multispectral imaging processing methodologies for analysing cultural heritage documents." Thesis, University College London (University of London), 2014. http://discovery.ucl.ac.uk/1427688/.

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Multispectral imaging is a method for acquiring image data over a series of wavelengths across the light spectrum. In combination with several image processing methods, it has become a valuable tool for the enhancement and recovery of information from cultural heritage documents. It enables the identification of distinct physical characteristics of the document and its material components by measuring their interaction with light. In this dissertation I describe an approach to evaluate multispectral imaging processing methods in the context of cultural heritage documents. I begin by framing a digital model, or phantom, of multispectral images of a document composed of interacting layers of text and other materials. Further, I apply a series of image processing methods to the phantom in order to extract and separate those interacting layers and I qualitatively assess the results of each of those methods. I proceed then to propose and apply a quantitative method, based on mutual information, to evaluate the efficacy of those image processing methods. Next, I describe the administration of a series of treatments that degrade the writing or otherwise degrade samples from a real document, and the acquisition of multispectral images from those samples. Finally, I report on the recovery of information via image processing of the acquired experimental data. The results of the image processing of the experimental data are then quantitatively evaluated using the proposed method, and qualitatively described. As multispectral imaging in combination with image processing methods become increasingly used in cultural heritage documents, we need a deeper understanding of how these methods perform in the analysis of this particular data. I contribute to this understanding in two important ways: I introduce a formal methodology to study the methods involved in processing and analysing the multispectral data, and provide a framework to continue testing and developing new methods.

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Earnshaw, Caroline Jane. "Sample preparation methodologies for MALDI-MS imaging and related topics." Thesis, Sheffield Hallam University, 2009. http://shura.shu.ac.uk/19590/.

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The diverse applications of MALDI MSI are explored in this thesis with an emphasis on the sample preparation procedure and method development for small molecule analysis for a range of samples. The two main themes that have been focussed on are the pharmaceutical and metabolomic applications of this state of the art technique. MALDI MSI has been evaluated as a technique for the detection and imaging of antiasthmatic compounds in lung tissue. Four compounds were assessed initially with conventional MALDI MS experiments, followed by both direct and indirect tissue imaging experiments. Pharmaceutical tablet formulations have also been assessed using MALDI MSI to map the active component throughout the excipients contained within the tablet providing information that is critical to the manufacturing process such as the homogeneity of the active pharmaceutical ingredient (API) throughout the tablet. MALDI MSI has been applied to the relatively new addition to the 'omics sciences, metabolomics. A non-targeted metabolomics approach has been used to study both plant and animal tissue in an attempt to gain a greater understanding of the complex biological processes that occur within both types of tissue. Wheat grain was used as the model system to conduct the experiments and evaluate the application of both UV MALDI MS and IR LDI MS for plant metabolomics. These techniques provided complementary information to published literature, however the novel aspect of this study was the incorporation of imaging experiments for UV MALDI MS; this allowed the metabolites to be visualised in the wheat grain section. MALDI MSI was also used to explore the differences between mice with chronic relapsing experimental autoimmune encephalomyelitis; the animal model of multiple sclerosis alongside healthy controls. Spinal cord samples were analysed and the main difference was tentatively attributed to choline levels.

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Ambadipudi, Kamalakar. "Assessment of Polarimetric Methodologies for Backscattered Imaging in Turbid Media." University of Akron / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=akron1236865442.

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Albaraki, Saeed Mohammed A. "Micromechanical analysis of pharmaceutical granules using advanced experimental imaging methodologies." Thesis, University of Leeds, 2015. http://etheses.whiterose.ac.uk/12207/.

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Fundamental level understandings on the processing behaviours of materials in granular and powder form is of high interest to number of engineering industries for example, mining, mineral, pharmaceutical, geotechnical and for advanced material processing applications. Handling and processing of pharmaceutical powders through confined geometries have very important role in pharmaceutical industry and many related powder process engineering sectors. Smooth flow of powders and granules mixtures from the feeding hopper to the compression chamber plays a very crucial role to achieve the integrity and quality of the final product. In this context, establishing clear understandings on the flow and compaction characteristics of particulates is vital. The mechanical behaviour of particulate materials such as powders and grains are different from the conventional states of matter. Depending on the loading levels and geometrical conditions, often they display combined features of solid, liquid and gaseous states. Though an extensive amount of studies are reported in the existing literatures on their mechanical response to loading, there are still a number of challenges to address: (i) Sensing stress distribution in particulate systems is not yet established especially when the size of the particulates are less than a millimetre (ii) Understanding is lacking on whether the stress distribution in initial static filling would influence the dynamic flow trajectories of the particulates when they are allowed to flow from the static state (iii) Micromechanical behaviour of particulates under low levels of external loading is still lacking and (iv) Interaction characteristics of stress and velocity distributions in particulate systems as a function of grain-scale properties and geometrical arrangements are still lacking. The present thesis addresses all of these important challenges in a systematic manner. The research is primarily based on the application of sensing stresses and displacements in particulates using advanced photo stress analysis tomography (PSAT), qualitative velocimetry using colour coding technique (CCT) and quantitative digital particle image velocimetry (DPIV). The required grain-scale properties are characterised comprehensively using a number of standard experimental methods. Where possible, experimental results on the stress and velocity distribution for particulate systems are compared with simulations using discrete element method (DEM) and analytical equations respectively, though the primary focus is on the experimental approaches. A number of outcomes from this research shed new lights and provide fundamental level understandings on the micromechanical properties of particulate systems with relevance to pharmaceutical granules processes.

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Asprey, Leonard Gregory. "An extension to system development methodologies for successful production imaging systems." Thesis, Queensland University of Technology, 2000.

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Kounalakis, Tsampikos. "Depth-adaptive methodologies for 3D image caregorization." Thesis, Brunel University, 2015. http://bura.brunel.ac.uk/handle/2438/11531.

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Image classification is an active topic of computer vision research. This topic deals with the learning of patterns in order to allow efficient classification of visual information. However, most research efforts have focused on 2D image classification. In recent years, advances of 3D imaging enabled the development of applications and provided new research directions. In this thesis, we present methodologies and techniques for image classification using 3D image data. We conducted our research focusing on the attributes and limitations of depth information regarding possible uses. This research led us to the development of depth feature extraction methodologies that contribute to the representation of images thus enhancing the recognition efficiency. We proposed a new classification algorithm that adapts to the need of image representations by implementing a scale-based decision that exploits discriminant parts of representations. Learning from the design of image representation methods, we introduced our own which describes each image by its depicting content providing more discriminative image representation. We also propose a dictionary learning method that exploits the relation of training features by assessing the similarity of features originating from similar context regions. Finally, we present our research on deep learning algorithms combined with data and techniques used in 3D imaging. Our novel methods provide state-of-the-art results, thus contributing to the research of 3D image classification.

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Guggenheim, Emily Jane. "Development of reflectance imaging methodologies to investigate super-paramagnetic iron oxide nanoparticles." Thesis, University of Birmingham, 2017. http://etheses.bham.ac.uk//id/eprint/7788/.

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Engineered nanoparticles, such as super paramagnetic iron oxide nanoparticles (SPIONs) offer significant benefits for the development of various diagnostic and therapeutic strategies. Limitations of existing imaging methodologies in the study of NPs, such as the effects of fluorescent labelling and diffraction limited resolution, and the advantages that visualization of spatial localization can offer in studies, increases the demand for new and optimized imaging routines. Reflectance Confocal Microscopy (RCM) methods were optimized and Reflectance Structured Illumination Microscopy (R-SIM) was introduced, offering a two fold increase in resolution - particularly advantageous for NP quantification and localization studies. Analysis routines were developed to enable the automated quantification of NP presence within cells via the different methodologies. Correlative procedures were also established for imaging the same sample with different reflectance methods and TEM, maximizing the information attainable from a single sample and allowing comparisons between the techniques for specific applications. These aforementioned optimized techniques were then applied to the determination of NP uptake and trafficking in cancer cell lines, and, in combination with siRNA, to ascertain proteins that are involved in the uptake process. Studies were also performed to model the degradative process of SPIONs within cellular compartments. This thesis thus provided several important tools for the future assessment of the efficacy and safety of NPs for clinical use, enabling quantitative analysis of uptake route, sub-cellular localization and NP intracellular fate.

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Baiotto, Ricardo. "Imaging methodologies applied on phased array ultrasonic data from austenitic welds and claddings." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2018. http://hdl.handle.net/10183/186162.

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A crescente tendência de utilização de materiais austeníticos soldados e cladeados em componentes críticos em alguns setores industriais, como nas indústrias de óleo&gás e nuclear, leva a um aumento na demanda sobre ensaios não-destrutivos confiáveis na avaliação de sua integridade estrutural. Dentre os métodos utilizados na inspeção de soldas cladeados austeníticos estão os métodos de ultrassom por phased array, que são normalmente utilizados na detecção e localização de defeitos. No entanto, componentes com esse tipo de microestrutura são difíceis de inspecionar por phased array devido a anisotropia e inomogeneidade causadas pela microestrutura de grãos grosseiros que costumam levar ao aumento do nível de ruído, ao deslocamento de indicações e ao surgimento de indicações falsas. Sendo assim, a seleção de um método de phased array apropriado precisa levar em conta a habilidade do método em superar os problemas causados pela anisotropia e inomogeneidade. Esta tese apresenta dois métodos de imagem por phased array ultrassônico não-convencionais pensados como formas de ajudar na determinação da integridade de componentes onde soldas e cladeados austeníticos estão presentes. Ambos os métodos tem como base o método de foco total (TFM), sendo que o primeiro é uma extensão do método de leis de atraso adaptativas chamado Método de Foco Total de Atraso Adaptativo (ADTFM) e o segundo método usa fatores de coerência associado à imagens de TFM. A partir dos métodos de imagem aplicados é possível aumentar significativamente a qualidade das imagens por ultrassom em comparação com as imagens padrão obtidas por TFM, especialmente quando foi possível utilizar ambos os métodos combinados.
The increasing trend to use austenitic welded and cladded materials in critical components employed in some industrial sectors, such as the oil&gas and nuclear industries, leads to an increasing demand for their non-destructive assessment by reliable non-destructive methods. Among the methods used to access the integrity of austenitic welds and claddings are the Ultrasonic Phased Array methods, which are usually used to detect the presence and determine the position of defects. However, austenitic welds and claddings are challenging to inspect with Phased Array methods due to the anisotropy and inhomogeneity caused by their coarse grain microstructure, which is capable of increasing noise levels, misplace indications and create false indications. Therefore, the selection of an appropriate phased array method needs to take into account the method’s ability to overcome the impairment caused by anisotropy and inhomogeneity. This thesis presents two non-conventional methods based on ultrasonic phased array imaging techniques designed to assist the structural integrity assessment of components where austenitic welds and clads are present. Both proposed methods are based on the Total Focusing Method (TFM); the first approach is an expansion of the adaptive delay laws concept named Adaptive Delay Total Focusing Method (ADTFM), while the second method uses the coherence weights combined with the TFM images. From the imaging methods applied it was possible to significantly increase the quality of the ultrasonic images in comparison with the standard TFM, primarily when it was possible to combine both approaches.

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Teh, Irvin Tze Wei. "Development of methodologies for diffusion-weighted magnetic resonance imaging at high field strength." Thesis, Imperial College London, 2009. http://hdl.handle.net/10044/1/4715.

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Diffusion-weighted imaging of small animals at high field strengths is a challenging prospect due to its extreme sensitivity to motion. Periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) was introduced at 9.4T as an imaging method that is robust to motion and distortion. Proton density (PD)-weighted and T2-weighted PROPELLER data were generally superior to that acquired with single-shot, Cartesian and echo planar imaging-based methods in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio and resistance to artifacts. Simulations and experiments revealed that PROPELLER image quality was dependent on the field strength and echo times specified. In particular, PD-weighted imaging at high field led to artifacts that reduced image contrast. In PROPELLER, data are acquired in progressively rotated blades in k-space and combined on a Cartesian grid. PROPELLER with echo truncation at low spatial frequencies (PETALS) was conceived as a post-processing method that improved contrast by reducing the overlap of k-space data from different blades with different echo times. Where the addition of diffusion weighting gradients typically leads to catastrophic motion artifacts in multi-shot sequences, diffusion-weighted PROPELLER enabled the acquisition of high quality, motion-robust data. Applications in the healthy mouse brain and abdomen at 9.4T and in stroke patients at 3T are presented. PROPELLER increases the minimum scan time by approximately 50%. Consequently, methods were explored to reduce the acquisition time. Two k-space undersampling regimes were investigated by examining image fidelity as a function of degree of undersampling. Undersampling by acquiring fewer k-space blades was shown to be more robust to motion and artifacts than undersampling by expanding the distance between successive phase encoding steps. To improve the consistency of undersampled data, the non-uniform fast Fourier transform was employed. It was found that acceleration factors of up to two could be used with minimal visual impact on image fidelity. To reduce the number of scans required for isotropic diffusion weighting, the use of rotating diffusion gradients was investigated, exploiting the rotational symmetry of the PROPELLER acquisition. Fixing the diffusion weighting direction to the individual rotating blades yielded geometry and anisotropy-dependent diffusion measurements. However, alternating the orientations of diffusion weighting with successive blades led to more accurate measurements of the apparent diffusion coefficient while halving the overall acquisition time. Optimized strategies are proposed for the use of PROPELLER in rapid high resolution imaging at high field strength.

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Books on the topic "Imaging methodologies"

1

K, Pal Sankar, and Peters James F, eds. Rough fuzzy image analysis: Foundations and methodologies. Boca Raton: Taylor & Francis, 2010.

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El-Baz, Ayman S. Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies: Volume 1. Boston, MA: Springer Science+Business Media, LLC, 2011.

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El-Baz, Ayman S. Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies: Volume II. New York, NY: Springer Science+Business Media, LLC, 2011.

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Kramer, Sharlotte L. B., and Rachael Tighe, eds. Thermomechanics & Infrared Imaging, Inverse Problem Methodologies and Mechanics of Additive & Advanced Manufactured Materials, Volume 7. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-59864-8.

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Tighe, Rachael C., John Considine, Sharlotte L. B. Kramer, and Tom Berfield, eds. Thermomechanics & Infrared Imaging, Inverse Problem Methodologies and Mechanics of Additive & Advanced Manufactured Materials, Volume 6. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-17475-9.

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Feng, Dong, Ghinea Gheorghita, and Chen Sherry Y, eds. User centered design for medical visualization. Hershey: Medical Information Science Reference, 2008.

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Kramer, Sharlotte L. B., Rachael Tighe, Ming-Tzer Lin, Cosme Furlong, and Chi-Hung Hwang, eds. Thermomechanics & Infrared Imaging, Inverse Problem Methodologies, Mechanics of Additive & Advanced Manufactured Materials, and Advancements in Optical Methods & Digital Image Correlation, Volume 4. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-86745-4.

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Camara, Oscar. Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges: Third International Workshop, STACOM 2012, Held in Conjunction with MICCAI 2012, Nice, France, October 5, 2012, Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Hillmer, Ansel T., Kelly P. Cosgrove, and Richard E. Carson. PET Brain Imaging Methodologies. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0009.

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While quantitative and pharmacologically specific aspects distinguish molecular imaging, they also impose the need for considerable expertise to design, conduct, and analyze molecular imaging studies. Positron emission tomography (PET) brain imaging provides a powerful noninvasive tool for quantitative and pharmacologically specific clinical research. This chapter describes basic methodological considerations for PET brain imaging studies. First the physiological interpretation of the most common outcome measures of binding potential (BPND) and volume of distribution (VT) are described. Next, aspects of acquisition of PET imaging data and blood measurements for analysis are discussed, followed by a summary of standard data analysis techniques. Finally, various applications for the study of mental illness, including group differences, measurements of drug occupancy, and assay of acute neurotransmitter release are discussed.

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Management, Information Resources. Medical Imaging: Concepts, Methodologies, Tools, and Applications. IGI Global, 2016.

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Book chapters on the topic "Imaging methodologies"

1

Buvat, Irène. "Methodologies for quantitative SPECT." In Physics of PET and SPECT Imaging, 195–210. Taylor & Francis Group, 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742: CRC Press, 2017. http://dx.doi.org/10.1201/9781315374383-11.

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Constantinides, Christakis. "Cardiac Multinuclear Imaging." In Protocols and Methodologies in Basic Science and Clinical Cardiac MRI, 215–36. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53001-7_6.

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Lavin Plaza, Begoña, Pierre Gebhardt, Alkystis Phinikaridou, and René M. Botnar. "Atherosclerotic Plaque Imaging." In Protocols and Methodologies in Basic Science and Clinical Cardiac MRI, 261–300. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53001-7_8.

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Cheng, Long, and Yi Gu. "An Image Compression Method Based on Compressive Sensing and Convolution Neural Network for Massive Imaging Flow Cytometry Data." In Intelligent Computing Methodologies, 755–66. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13832-4_62.

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Kawahara, Masahiro. "Chemical Reaction Engineering Methodologies for Biomedical Imaging Analysis." In Biomedical Engineering Challenges, 119–44. Chichester, UK: John Wiley & Sons, Ltd, 2018. http://dx.doi.org/10.1002/9781119296034.ch7.

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Podo, F. "General Need for Quantitative Methodologies in Tissue Characterization by MRI." In Tissue Characterization in MR Imaging, 7–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-74993-3_2.

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Mostapha, Mahmoud, Fahmi Khalifa, Amir Alansary, Ahmed Soliman, Jasjit Suri, and Ayman S. El-Baz. "Computer-Aided Diagnosis Systems for Acute Renal Transplant Rejection: Challenges and Methodologies." In Abdomen and Thoracic Imaging, 1–35. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-8498-1_1.

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Costa, J. Miguel, O. M. Grant, and M. M. Chaves. "Use of Thermal Imaging in Viticulture: Current Application and Future Prospects." In Methodologies and Results in Grapevine Research, 135–50. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-9283-0_10.

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Miller, Jack J. "Myocyte Metabolic Imaging with Hyperpolarised MRI." In Protocols and Methodologies in Basic Science and Clinical Cardiac MRI, 111–73. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53001-7_4.

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Lee, Wook, Byungkyu Park, and Kyungsook Han. "SVM-Based Classification of Diffusion Tensor Imaging Data for Diagnosing Alzheimer’s Disease and Mild Cognitive Impairment." In Intelligent Computing Theories and Methodologies, 489–99. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22186-1_49.

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Conference papers on the topic "Imaging methodologies"

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Salucci, Marco, Samantha Lusa, Lorenzo Poli, Alessandro Polo, Luca Tosi, and Andrea Massa. "AI-Based Methodologies for Next-Generation Biomedical Imaging: Recent Advances and Future Trends." In 2024 9th International Conference on Smart and Sustainable Technologies (SpliTech), 1–3. IEEE, 2024. http://dx.doi.org/10.23919/splitech61897.2024.10612417.

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Mosca, Nicola, Maria di Summa, Moh Rafik, Vittorio Bianco, Daniele Pirone, and Ettore Stella. "Immersive Exploration of Tomographic Datasets: Virtual Reality Revolutionizing Microscopic Analysis." In Digital Holography and Three-Dimensional Imaging, W2B.5. Washington, D.C.: Optica Publishing Group, 2024. http://dx.doi.org/10.1364/dh.2024.w2b.5.

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Traditional microscopy has limitations. On the contrary, tomographic methods provide non-destructive 3D visualization. This paper proposes immersive exploration via virtual reality, revolutionizing scientific analysis by bridging traditional techniques with advanced methodologies for enhanced research insights.

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Distante, Cosimo, Pierluigi Carcagni, Andouglas Gonçalves da Silva Júnior, and Luiz Marcos Garcia Gonçalves. "EREMITE: A marinE infRastructurE to MonItor the sTate of the sEas." In Digital Holography and Three-Dimensional Imaging, Tu5B.2. Washington, D.C.: Optica Publishing Group, 2024. http://dx.doi.org/10.1364/dh.2024.tu5b.2.

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EREMITE is a low-cost and open multi-sensory system that monitors and digitises our coastal marine ecosystems to understand their state, ecological health and functioning, with the concept of any sensor, anytime, anywhere. It is made of an optical multi-sensing system onboard an autonomous sailboat that perceives and reasons about underwater abiotic and biotic conditions of our critical natural resources. Besides standard water quality parameters acquired with COTS optical sensors, the drone implements a digital holographic microscope, able to detect in real-time micro-plastics and diatoms. The task of diatom classification and microplastics detection of particles flowing in the micro-channel occurs with deep learning methodologies, which have proven to perform reliably, as shown by the computed metrics.

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Sitnik, Robert, and Malgorzata Kujawinska. "Creating true 3D-shape representation: merging methodologies." In Electronic Imaging 2002, edited by Brian D. Corner, Roy P. Pargas, and Joseph H. Nurre. SPIE, 2002. http://dx.doi.org/10.1117/12.460163.

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Salucci, Marco, Federico Boulos, Maokun Li, Giulia Mansutti, Davide Marcantonio, and Andrea Massa. "Innovative Methodologies for Chest Medical Imaging." In 2019 IEEE Asia-Pacific Microwave Conference (APMC). IEEE, 2019. http://dx.doi.org/10.1109/apmc46564.2019.9038370.

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Akhtar, M. J., Greeshmaja Govind, and Zubair Akhter. "Microwave Subsurface Imaging: Methodologies and Applications." In 2019 URSI Asia-Pacific Radio Science Conference (AP-RASC). IEEE, 2019. http://dx.doi.org/10.23919/ursiap-rasc.2019.8738221.

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Demigha, Souad, and Colette Rolland. "Training-aided system in senology: methodologies and techniques." In Medical Imaging 2003, edited by H. K. Huang and Osman M. Ratib. SPIE, 2003. http://dx.doi.org/10.1117/12.480460.

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Trewin, B., M. Wiseman, and E. Oguz. "Digital core imaging - Methodologies, benefits and application." In 58th EAEG Meeting. Netherlands: EAGE Publications BV, 1996. http://dx.doi.org/10.3997/2214-4609.201408973.

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Saunders, David, Richard Collmann, and Ann Borda. "Reflectance Transformation Imaging and ImageJ: Comparing Imaging Methodologies for Cultural Heritage Artefacts." In Electronic Visualisation and the Arts (EVA 2017). BCS Learning & Development, 2017. http://dx.doi.org/10.14236/ewic/eva2017.71.

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Paquerault, Sophie, Frank W. Samuelson, Nicholas Petrick, and Kyle J. Myers. "Comparing signal-based and case-based methodologies for CAD assessment in a detection task." In Medical Imaging, edited by Berkman Sahiner and David J. Manning. SPIE, 2008. http://dx.doi.org/10.1117/12.771498.

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Reports on the topic "Imaging methodologies"

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Spencer. PR-185-084501-R01 Technologies and Methodology for Automated Ultrasonic Testing Systems Quantification. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), April 2011. http://dx.doi.org/10.55274/r0010725.

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For automated ultrasonic testing (AUT) detection and sizing accuracy, this program developed a methodology for quantification of AUT systems, advancing and quantifying AUT systems image-capture capabilities, quantifying the performance of multiple AUT systems, establishing a guidance document, conducting field tests, and delivering a guidance document for future inclusion in reliability-based design and assessment (RBDA) standards. Improvements for AUT of pipeline girth welds were identified by investigating: imaging techniques for AUT data, modeling and simulation tools for AUT technique development and validation, and quantification methodologies for measuring the performance of AUT systems. Throughout the course of the project, many AUT scans were conducted using both zonal and non-zonal inspection techniques. The quantification methodology provides guidance for quantifying the performance of AUT systems with respect to probability of detection (POD) and accuracy of flaw sizing. Field trials and lab trials demonstrated that a sector sweep of beam angles provides alternative imaging capabilities that may enhance current zonal techniques. Current methodologies used for quantifying detection and sizing limits for AUT systems vary and produce great variability in detection and sizing results. Consequently, a standardized quantification approach is recommended to reduce this variability. This investigation evaluated six AUT systems; flaw heights were detected between 2 and 4 mm with a 90% probability and a confidence level of 95% (a90/95). The use of ultrasonic modeling and inspection simulation software provided a good tool for developing and evaluating AUT procedures; and can be used to evaluate changes in essential variables.

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Author, Unknown. L52297 Technologies for In-Service Measurement of Seal Gaps in Internal Floating Roof Tanks. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), June 2009. http://dx.doi.org/10.55274/r0010683.

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The industry need was to investigate current and potential technologies for the measurement of seal gaps in internal floating roof storage tanks, including methods of remote monitoring including a) identify existing seal gap measurement technologies and methodologies as well as individuals and/or companies who own the technologies, and b) identify other technologies that may prove useful to effectively measure seal gaps on tanks in service. Four technologies were identified as possible remote-inspection alternatives to the current general practice of inspecting and measuring internal floating roof seal gaps by placing personnel inside in-service tanks. At least two of these technologies, remote camera and x-ray imaging, are worthy of additional evaluation to assess the relative costs and reliability as alternatives to manual inspection and measurement. Remote camera technology has been applied specifically to seal gap measurement and shown to be a viable alternative to manual inspection. X-ray imaging technology appears to be viable as an alternative but has not been applied specifically to seal gap measurement and would require further development to affirm its suitability for this purpose..

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Anderson, Gerald L., and Kalman Peleg. Precision Cropping by Remotely Sensed Prorotype Plots and Calibration in the Complex Domain. United States Department of Agriculture, December 2002. http://dx.doi.org/10.32747/2002.7585193.bard.

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This research report describes a methodology whereby multi-spectral and hyperspectral imagery from remote sensing, is used for deriving predicted field maps of selected plant growth attributes which are required for precision cropping. A major task in precision cropping is to establish areas of the field that differ from the rest of the field and share a common characteristic. Yield distribution f maps can be prepared by yield monitors, which are available for some harvester types. Other field attributes of interest in precision cropping, e.g. soil properties, leaf Nitrate, biomass etc. are obtained by manual sampling of the filed in a grid pattern. Maps of various field attributes are then prepared from these samples by the "Inverse Distance" interpolation method or by Kriging. An improved interpolation method was developed which is based on minimizing the overall curvature of the resulting map. Such maps are the ground truth reference, used for training the algorithm that generates the predicted field maps from remote sensing imagery. Both the reference and the predicted maps are stratified into "Prototype Plots", e.g. 15xl5 blocks of 2m pixels whereby the block size is 30x30m. This averaging reduces the datasets to manageable size and significantly improves the typically poor repeatability of remote sensing imaging systems. In the first two years of the project we used the Normalized Difference Vegetation Index (NDVI), for generating predicted yield maps of sugar beets and com. The NDVI was computed from image cubes of three spectral bands, generated by an optically filtered three camera video imaging system. A two dimensional FFT based regression model Y=f(X), was used wherein Y was the reference map and X=NDVI was the predictor. The FFT regression method applies the "Wavelet Based", "Pixel Block" and "Image Rotation" transforms to the reference and remote images, prior to the Fast - Fourier Transform (FFT) Regression method with the "Phase Lock" option. A complex domain based map Yfft is derived by least squares minimization between the amplitude matrices of X and Y, via the 2D FFT. For one time predictions, the phase matrix of Y is combined with the amplitude matrix ofYfft, whereby an improved predicted map Yplock is formed. Usually, the residuals of Y plock versus Y are about half of the values of Yfft versus Y. For long term predictions, the phase matrix of a "field mask" is combined with the amplitude matrices of the reference image Y and the predicted image Yfft. The field mask is a binary image of a pre-selected region of interest in X and Y. The resultant maps Ypref and Ypred aremodified versions of Y and Yfft respectively. The residuals of Ypred versus Ypref are even lower than the residuals of Yplock versus Y. The maps, Ypref and Ypred represent a close consensus of two independent imaging methods which "view" the same target. In the last two years of the project our remote sensing capability was expanded by addition of a CASI II airborne hyperspectral imaging system and an ASD hyperspectral radiometer. Unfortunately, the cross-noice and poor repeatability problem we had in multi-spectral imaging was exasperated in hyperspectral imaging. We have been able to overcome this problem by over-flying each field twice in rapid succession and developing the Repeatability Index (RI). The RI quantifies the repeatability of each spectral band in the hyperspectral image cube. Thereby, it is possible to select the bands of higher repeatability for inclusion in the prediction model while bands of low repeatability are excluded. Further segregation of high and low repeatability bands takes place in the prediction model algorithm, which is based on a combination of a "Genetic Algorithm" and Partial Least Squares", (PLS-GA). In summary, modus operandi was developed, for deriving important plant growth attribute maps (yield, leaf nitrate, biomass and sugar percent in beets), from remote sensing imagery, with sufficient accuracy for precision cropping applications. This achievement is remarkable, given the inherently high cross-noice between the reference and remote imagery as well as the highly non-repeatable nature of remote sensing systems. The above methodologies may be readily adopted by commercial companies, which specialize in proving remotely sensed data to farmers.

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