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Computer Vision For Biomedical Image Applications


Computer Vision For Biomedical Image Applications
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Computer Vision For Biomedical Image Applications


Computer Vision For Biomedical Image Applications
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Author : Yanxi Liu
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-10-10

Computer Vision For Biomedical Image Applications written by Yanxi Liu 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 2005-10-10 with Computers categories.


This book constitutes the refereed proceedings of the First International Workshop on Computer Vision for Biomedical Image Applications: Current Techniques and Future Trends, CVBIA 2005, held in Beijing, China, in October 2005 within the scope of ICCV 20.



Deep Learning For Medical Image Analysis


Deep Learning For Medical Image Analysis
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Author : S. Kevin Zhou
language : en
Publisher: Academic Press
Release Date : 2023-11-23

Deep Learning For Medical Image Analysis written by S. Kevin Zhou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-23 with Computers categories.


Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for academic and industry researchers and graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Deep learning provides exciting solutions for medical image analysis problems and is a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component are applied to medical image detection, segmentation, registration, and computer-aided analysis. - Covers common research problems in medical image analysis and their challenges - Describes the latest deep learning methods and the theories behind approaches for medical image analysis - Teaches how algorithms are applied to a broad range of application areas including cardiac, neural and functional, colonoscopy, OCTA applications and model assessment· Includes a Foreword written by Nicholas Ayache



Computer Vision And Machine Intelligence In Medical Image Analysis


Computer Vision And Machine Intelligence In Medical Image Analysis
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Author : Mousumi Gupta
language : en
Publisher: Springer Nature
Release Date : 2019-08-28

Computer Vision And Machine Intelligence In Medical Image Analysis written by Mousumi Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-28 with Technology & Engineering categories.


This book includes high-quality papers presented at the Symposium 2019, organised by Sikkim Manipal Institute of Technology (SMIT), in Sikkim from 26–27 February 2019. It discusses common research problems and challenges in medical image analysis, such as deep learning methods. It also discusses how these theories can be applied to a broad range of application areas, including lung and chest x-ray, breast CAD, microscopy and pathology. The studies included mainly focus on the detection of events from biomedical signals.



Decision Forests For Computer Vision And Medical Image Analysis


Decision Forests For Computer Vision And Medical Image Analysis
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Author : Antonio Criminisi
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-01-30

Decision Forests For Computer Vision And Medical Image Analysis written by Antonio Criminisi 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 2013-01-30 with Computers categories.


This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision forests; discusses the use of decision forests for such tasks as classification, regression, density estimation, manifold learning, active learning and semi-supervised classification; includes exercises and experiments throughout the text, with solutions, slides, demo videos and other supplementary material provided at an associated website; provides a free, user-friendly software library, enabling the reader to experiment with forests in a hands-on manner.



Biomedical Image Analysis And Machine Learning Technologies Applications And Techniques


Biomedical Image Analysis And Machine Learning Technologies Applications And Techniques
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Author : Gonzalez, Fabio A.
language : en
Publisher: IGI Global
Release Date : 2009-12-31

Biomedical Image Analysis And Machine Learning Technologies Applications And Techniques written by Gonzalez, Fabio A. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-31 with Computers categories.


Medical images are at the base of many routine clinical decisions and their influence continues to increase in many fields of medicine. Since the last decade, computers have become an invaluable tool for supporting medical image acquisition, processing, organization and analysis. Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques provides a panorama of the current boundary between biomedical complexity coming from the medical image context and the multiple techniques which have been used for solving many of these problems. This innovative publication serves as a leading industry reference as well as a source of creative ideas for applications of medical issues.



Multi Modality State Of The Art Medical Image Segmentation And Registration Methodologies


Multi Modality State Of The Art Medical Image Segmentation And Registration Methodologies
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Author : Ayman S. El-Baz
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-04-11

Multi Modality State Of The Art Medical Image Segmentation And Registration Methodologies written by Ayman S. El-Baz 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 2011-04-11 with Medical categories.


With the advances in image guided surgery for cancer treatment, the role of image segmentation and registration has become very critical. The central engine of any image guided surgery product is its ability to quantify the organ or segment the organ whether it is a magnetic resonance imaging (MRI) and computed tomography (CT), X-ray, PET, SPECT, Ultrasound, and Molecular imaging modality. Sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures present in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning system designs. The focus of this book in towards the state of the art techniques in the area of image segmentation and registration.



Intelligent Computing Techniques In Biomedical Imaging


Intelligent Computing Techniques In Biomedical Imaging
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Author : Bikesh Kumar Singh
language : en
Publisher: Elsevier
Release Date : 2024-08-23

Intelligent Computing Techniques In Biomedical Imaging written by Bikesh Kumar Singh and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-23 with Science categories.


Intelligent Computing Techniques in Biomedical Imaging provides comprehensive and state-of-the-art applications of Computational Intelligence techniques used in biomedical image analysis for disease detection and diagnosis. The book offers readers a stepwise approach from fundamental to advanced techniques using real-life medical examples and tutorials. The editors have divided the book into five sections, from prerequisites to case studies.Section I presents the prerequisites, where the reader will find fundamental concepts needed for advanced topics covered later in this book. This primarily includes a thorough introduction to Artificial Intelligence, probability theory and statistical learning. The second section covers Computational Intelligence methods for medical image acquisition and pre-processing for biomedical images. In this section, readers will find AI applied to conventional and advanced biomedical imaging modalities such as X-rays, CT scan, MRI, Mammography, Ultrasound, MR Spectroscopy, Positron Emission Tomography (PET), Ultrasound Elastography, Optical Coherence Tomography (OCT), Functional MRI, Hybrid Modalities, as well as pre-processing topics such as medical image enhancement, segmentation, and compression. Section III covers description and representation of medical images. Here the reader will find various categories of features and their relevance in different medical imaging tasks. This section also discusses feature selection techniques based on filter method, wrapper method, embedded method, and more.The fourth section covers Computational Intelligence techniques used for medical image classification, including Artificial Neural Networks, Support Vector Machines, Decision Trees, Nearest Neighbor Classifiers, Random Forest, clustering, extreme learning, Convolution Neural Networks (CNN), and Recurrent Neural Networks. This section also includes a discussion of computer aided diagnosis and performance evaluation in radiology.The final section of Intelligent Computing Techniques in Biomedical Imaging provides readers with a wealth of real-world Case Studies for Computational Intelligence techniques in applications such as neuro-developmental disorders, brain tumor detection, breast cancer detection, bone fracture detection, pulmonary imaging, thyroid disorders, imaging technologies in dentistry, diagnosis of ocular diseases, cardiovascular imaging, and multimodal imaging. - Introduces Fourier theory and signal analysis tailored to applications in optical communications devices and systems - Provides strong theoretical background, making it a ready resource for researchers and advanced students in optical communication and optical signal processing - Starts from basic theory and then develops descriptions of useful applications



Computational Vision And Medical Image Processing Iv


Computational Vision And Medical Image Processing Iv
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Author : Joao Manuel RS Tavares
language : en
Publisher: CRC Press
Release Date : 2013-10-01

Computational Vision And Medical Image Processing Iv written by Joao Manuel RS Tavares and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-01 with Computers categories.


Computational Vision and Medical Image Processing. VIPIMAGE 2013 contains invited lectures and full papers presented at VIPIMAGE 2013 - IV ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing (Funchal, Madeira Island, Portugal, 14-16 October 2013). International contributions from 16 countries provide a comprehensive coverage of the current state-of-the-art in the fields of: 3D Vision; Computational Bioimaging and Visualization; Computational Vision and Image Processing applied to Dental Medicine; Computational Vision; Computer Aided Diagnosis, Surgery, Therapy, and Treatment; Data Interpolation, Registration, Acquisition and Compression; Image Processing and Analysis; Image Segmentation; Imaging of Biological Flows; Medical Imaging; Physics of Medical Imaging; Shape Reconstruction; Signal Processing; Simulation and Modeling; Software Development for Image Processing and Analysis; Telemedicine Systems and their Applications; Trabecular Bone Characterization; Tracking and Analysis of Movement; Virtual Reality. Related techniques covered in this book include the level set method, finite element method, modal analyses, stochastic methods, principal and independent components analysis and distribution models. Computational Vision and Medical Image Processing. VIPIMAGE 2013 is useful to academics, researchers and professionals in Biomechanics, Biomedical Engineering, Computational Vision (image processing and analysis), Computer Sciences, Computational Mechanics and Medicine.



Diagnostic Biomedical Signal And Image Processing Applications With Deep Learning Methods


Diagnostic Biomedical Signal And Image Processing Applications With Deep Learning Methods
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Author : Kemal Polat
language : en
Publisher: Elsevier
Release Date : 2023-04-30

Diagnostic Biomedical Signal And Image Processing Applications With Deep Learning Methods written by Kemal Polat and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-30 with Computers categories.


Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods presents comprehensive research on both medical imaging and medical signals analysis. The book discusses classification, segmentation, detection, tracking and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT and X-RAY, amongst others. These image and signal modalities include real challenges that are the main themes that medical imaging and medical signal processing researchers focus on today. The book also emphasizes removing noise and specifying dataset key properties, with each chapter containing details of one of the medical imaging or medical signal modalities. Focusing on solving real medical problems using new deep learning and CNN approaches, this book will appeal to research scholars, graduate students, faculty members, R&D engineers, and biomedical engineers who want to learn how medical signals and images play an important role in the early diagnosis and treatment of diseases. - Investigates novel concepts of deep learning for acquisition of non-invasive biomedical image and signal modalities for different disorders - Explores the implementation of novel deep learning and CNN methodologies and their impact studies that have been tested on different medical case studies - Presents end-to-end CNN architectures for automatic detection of situations where early diagnosis is important - Includes novel methodologies, datasets, design and simulation examples



Handbook Of Medical Image Computing And Computer Assisted Intervention


Handbook Of Medical Image Computing And Computer Assisted Intervention
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Author : S. Kevin Zhou
language : en
Publisher: Academic Press
Release Date : 2019-10-18

Handbook Of Medical Image Computing And Computer Assisted Intervention written by S. Kevin Zhou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-18 with Computers categories.


Handbook of Medical Image Computing and Computer Assisted Intervention presents important advanced methods and state-of-the art research in medical image computing and computer assisted intervention, providing a comprehensive reference on current technical approaches and solutions, while also offering proven algorithms for a variety of essential medical imaging applications. This book is written primarily for university researchers, graduate students and professional practitioners (assuming an elementary level of linear algebra, probability and statistics, and signal processing) working on medical image computing and computer assisted intervention. - Presents the key research challenges in medical image computing and computer-assisted intervention - Written by leading authorities of the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society - Contains state-of-the-art technical approaches to key challenges - Demonstrates proven algorithms for a whole range of essential medical imaging applications - Includes source codes for use in a plug-and-play manner - Embraces future directions in the fields of medical image computing and computer-assisted intervention