Texture Analysis Applied To Second Harmonic Generation Image Data For Disease Classification And Development Of A Multi View Second Harmonic Generation Imaging Platform
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Texture Analysis Applied To Second Harmonic Generation Image Data For Disease Classification And Development Of A Multi View Second Harmonic Generation Imaging Platform
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Author :
language : en
Publisher:
Release Date : 2016
Texture Analysis Applied To Second Harmonic Generation Image Data For Disease Classification And Development Of A Multi View Second Harmonic Generation Imaging Platform written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Many diseases, e.g. ovarian cancer, breast cancer and pulmonary fibrosis, are commonly associated with drastic alterations in surrounding connective tissue, and changes in the extracellular matrix (ECM) are associated with the vast majority of cellular processes in disease progression and carcinogenesis: cell differentiation, proliferation, biosynthetic ability, polarity, and motility. We use second harmonic generation (SHG) microscopy for imaging the ECM because it is a non-invasive, non-linear laser scanning technique with high sensitivity and specificity for visualizing fibrillar collagen. In this thesis, we are interested in developing imaging techniques to understand how the ECM, especially the collagen architecture, is remodeled in diseases To quantitate remodeling, we implement a 3D texture analysis to delineate the collagen fibrillar morphology observed in SHG microscopy images of human normal and high grade malignant ovarian tissues. In the learning stage, a dictionary of "textons"--Frequently occurring texture features that are identified by measuring the image response to a filter bank of various shapes, sizes, and orientations--is created. By calculating a representative model based on the texton distribution for each tissue type using a training set of respective mages, we then perform classification between normal and high grade malignant ovarian tissues classification based on the area under receiver operating characteristic curves (true positives versus false positives). The local analysis algorithm is a more general method to probe rapidly changing fibrillar morphologies than global analyses such as FFT. It is also more versatile than other texture approaches as the filter bank can be highly tailored to specific applications (e.g., different disease states) by creating customized libraries based on common image features. Further, we describe the development of a multi-view 3D SHG imaging platform. Unlike fluorescence microscopy, SHG excites intrinsic characteristics of collagen, bypassing the need for additional primary and secondary imaging labels. However, single view image collection from endogenous SHG contrast of collagen molecules is not "a true 3D technique," because collagen fibers oriented along the plane of the lasers used to excite them are invisible to the excitation The loss of information means that researchers cannot resolve the 3D structure of the ECM using this technique. We are developing a new, multi-view approach that involves rotation of agarose embedded sample in FEP tubing, so that the excitation beam path travels to from multiple angles, to reveal new insight in understanding the 3D collagen structure and its role in normal and diseased tissue
Handbook Of Texture Analysis
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Author : Ayman El-Baz
language : en
Publisher: CRC Press
Release Date : 2024-06-21
Handbook Of Texture Analysis written by Ayman El-Baz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-21 with Computers categories.
The major goals of texture research in computer vision are to understand, model, and process texture and, ultimately, to simulate the human visual learning process using computer technologies. In the last decade, artificial intelligence has been revolutionized by machine learning and big data approaches, outperforming human prediction on a wide range of problems. In particular, deep learning convolutional neural networks (CNNs) are particularly well suited to texture analysis. This volume presents important branches of texture analysis methods which find a proper application in AI-based medical image analysis. This book: Discusses first-order, second-order statistical methods, local binary pattern (LBP) methods, and filter bank-based methods Covers spatial frequency-based methods, Fourier analysis, Markov random fields, Gabor filters, and Hough transformation Describes advanced textural methods based on DL as well as BD and advanced applications of texture to medial image segmentation Is aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineering This is an essential reference for those looking to advance their understanding in this applied and emergent field.
Biomedical Texture Analysis
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Author : Adrien Depeursinge
language : en
Publisher: Academic Press
Release Date : 2017-08-25
Biomedical Texture Analysis written by Adrien Depeursinge and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-25 with Computers categories.
Biomedical Texture Analysis: Fundamentals, Applications, Tools and Challenges describes the fundamentals and applications of biomedical texture analysis (BTA) for precision medicine. It defines what biomedical textures (BTs) are and why they require specific image analysis design approaches when compared to more classical computer vision applications. The fundamental properties of BTs are given to highlight key aspects of texture operator design, providing a foundation for biomedical engineers to build the next generation of biomedical texture operators. Examples of novel texture operators are described and their ability to characterize BTs are demonstrated in a variety of applications in radiology and digital histopathology. Recent open-source software frameworks which enable the extraction, exploration and analysis of 2D and 3D texture-based imaging biomarkers are also presented. This book provides a thorough background on texture analysis for graduate students and biomedical engineers from both industry and academia who have basic image processing knowledge. Medical doctors and biologists with no background in image processing will also find available methods and software tools for analyzing textures in medical images. Defines biomedical texture precisely and describe how it is different from general texture information considered in computer vision Defines the general problem to translate 2D and 3D texture patterns from biomedical images to visually and biologically relevant measurements Describes, using intuitive concepts, how the most popular biomedical texture analysis approaches (e.g., gray-level matrices, fractals, wavelets, deep convolutional neural networks) work, what they have in common, and how they are different Identifies the strengths, weaknesses, and current challenges of existing methods including both handcrafted and learned representations, as well as deep learning. The goal is to establish foundations for building the next generation of biomedical texture operators Showcases applications where biomedical texture analysis has succeeded and failed Provides details on existing, freely available texture analysis software, helping experts in medicine or biology develop and test precise research hypothesis
Second Harmonic Generation Imaging
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Author : Francesco S. Pavone
language : en
Publisher: Taylor & Francis
Release Date : 2016-04-19
Second Harmonic Generation Imaging written by Francesco S. Pavone and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Science categories.
Second-harmonic generation (SHG) microscopy has shown great promise for imaging live cells and tissues, with applications in basic science, medical research, and tissue engineering. Second Harmonic Generation Imaging offers a complete guide to this optical modality, from basic principles, instrumentation, methods, and image analysis to biomedical a
Handbook Of Texture Analysis
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Author : Ayman El-Baz
language : en
Publisher:
Release Date : 2024-04
Handbook Of Texture Analysis written by Ayman El-Baz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04 with categories.
This two-volume handbook provides a comprehensive view of texture analysis in both AI-based industrial and medical imaging applications. The first volume covers texture analysis for neuroradiology; information-theoretic entropy; chronic liver diseases; clinical management of focal liver lesions; abdominal imaging; optical coherence tomography images; thoracic imaging; prostate cancer; breast cancer; bladder cancer, quality evaluation of meat products; and detection of powdery mildew on strawberry leaves. The second volume covers Local Binary Descriptors for Texture Classification; Precision Grading of Glioma; Liver Tumor Detection and Grading; Texture Analysis in Radiology; Texture Analysis Using a Self-Organizing Feature Map; Sensor-Based Human Activity Recognition Analysis Using Machine Learning and Topological Data Analysis; Texture Analysis in Retinal OCT Imaging; Pneumonia Detection; Prostatic Adenocarcinoma; and Texture Analysis in Cancer Prognosis. Aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineering, this handbook is an essential reference for those looking to advance their understanding in this applied and emergent field.
Texture Feature Extraction Techniques For Image Recognition
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Author : Jyotismita Chaki
language : en
Publisher: Springer Nature
Release Date : 2019-10-24
Texture Feature Extraction Techniques For Image Recognition written by Jyotismita Chaki and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-24 with Technology & Engineering categories.
The book describes various texture feature extraction approaches and texture analysis applications. It introduces and discusses the importance of texture features, and describes various types of texture features like statistical, structural, signal-processed and model-based. It also covers applications related to texture features, such as facial imaging. It is a valuable resource for machine vision researchers and practitioners in different application areas.
Classification Techniques For Medical Image Analysis And Computer Aided Diagnosis
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Author : Nilanjan Dey
language : en
Publisher: Academic Press
Release Date : 2019-07-31
Classification Techniques For Medical Image Analysis And Computer Aided Diagnosis written by Nilanjan Dey and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-31 with Science categories.
Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images.
Visualizing Chemistry
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2006-06-01
Visualizing Chemistry written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-06-01 with Science categories.
Scientists and engineers have long relied on the power of imaging techniques to help see objects invisible to the naked eye, and thus, to advance scientific knowledge. These experts are constantly pushing the limits of technology in pursuit of chemical imagingâ€"the ability to visualize molecular structures and chemical composition in time and space as actual events unfoldâ€"from the smallest dimension of a biological system to the widest expanse of a distant galaxy. Chemical imaging has a variety of applications for almost every facet of our daily lives, ranging from medical diagnosis and treatment to the study and design of material properties in new products. In addition to highlighting advances in chemical imaging that could have the greatest impact on critical problems in science and technology, Visualizing Chemistry reviews the current state of chemical imaging technology, identifies promising future developments and their applications, and suggests a research and educational agenda to enable breakthrough improvements.
Cellular Image Classification
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Author : Xiang Xu
language : en
Publisher: Springer
Release Date : 2016-11-24
Cellular Image Classification written by Xiang Xu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-24 with Technology & Engineering categories.
This book introduces new techniques for cellular image feature extraction, pattern recognition and classification. The authors use the antinuclear antibodies (ANAs) in patient serum as the subjects and the Indirect Immunofluorescence (IIF) technique as the imaging protocol to illustrate the applications of the described methods. Throughout the book, the authors provide evaluations for the proposed methods on two publicly available human epithelial (HEp-2) cell datasets: ICPR2012 dataset from the ICPR'12 HEp-2 cell classification contest and ICIP2013 training dataset from the ICIP'13 Competition on cells classification by fluorescent image analysis. First, the reading of imaging results is significantly influenced by one’s qualification and reading systems, causing high intra- and inter-laboratory variance. The authors present a low-order LP21 fiber mode for optical single cell manipulation and imaging staining patterns of HEp-2 cells. A focused four-lobed mode distribution is stable and effective in optical tweezer applications, including selective cell pick-up, pairing, grouping or separation, as well as rotation of cell dimers and clusters. Both translational dragging force and rotational torque in the experiments are in good accordance with the theoretical model. With a simple all-fiber configuration, and low peak irradiation to targeted cells, instrumentation of this optical chuck technology will provide a powerful tool in the ANA-IIF laboratories. Chapters focus on the optical, mechanical and computing systems for the clinical trials. Computer programs for GUI and control of the optical tweezers are also discussed. to more discriminative local distance vector by searching for local neighbors of the local feature in the class-specific manifolds. Encoding and pooling the local distance vectors leads to salient image representation. Combined with the traditional coding methods, this method achieves higher classification accuracy. Then, a rotation invariant textural feature of Pairwise Local Ternary Patterns with Spatial Rotation Invariant (PLTP-SRI) is examined. It is invariant to image rotations, meanwhile it is robust to noise and weak illumination. By adding spatial pyramid structure, this method captures spatial layout information. While the proposed PLTP-SRI feature extracts local feature, the BoW framework builds a global image representation. It is reasonable to combine them together to achieve impressive classification performance, as the combined feature takes the advantages of the two kinds of features in different aspects. Finally, the authors design a Co-occurrence Differential Texton (CoDT) feature to represent the local image patches of HEp-2 cells. The CoDT feature reduces the information loss by ignoring the quantization while it utilizes the spatial relations among the differential micro-texton feature. Thus it can increase the discriminative power. A generative model adaptively characterizes the CoDT feature space of the training data. Furthermore, exploiting a discriminant representation allows for HEp-2 cell images based on the adaptive partitioned feature space. Therefore, the resulting representation is adapted to the classification task. By cooperating with linear Support Vector Machine (SVM) classifier, this framework can exploit the advantages of both generative and discriminative approaches for cellular image classification. The book is written for those researchers who would like to develop their own programs, and the working MatLab codes are included for all the important algorithms presented. It can also be used as a reference book for graduate students and senior undergraduates in the area of biomedical imaging, image feature extraction, pattern recognition and classification. Academics, researchers, and professional will find this to be an exceptional resource.
Microscopy Techniques
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Author : Jens Rietdorf
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-06-23
Microscopy Techniques written by Jens Rietdorf and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-06-23 with Science categories.
With contributions by numerous experts