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Computing And Visualization For Intravascular Imaging And Computer Assisted Stenting

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Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting

Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting Book
Author : Simone Balocco,Maria A. Zuluaga,Guillaume Zahnd,Su-Lin Lee,Stefanie Demirci
Publisher : Academic Press
Release : 2016-12-12
ISBN : 0128110198
Language : En, Es, Fr & De

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Book Description :

Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting presents imaging, treatment, and computed assisted technological techniques for diagnostic and intraoperative vascular imaging and stenting. These techniques offer increasingly useful information on vascular anatomy and function, and are poised to have a dramatic impact on the diagnosis, analysis, modeling, and treatment of vascular diseases. After setting out the technical and clinical challenges of vascular imaging and stenting, the book gives a concise overview of the basics before presenting state-of-the-art methods for solving these challenges. Readers will learn about the main challenges in endovascular procedures, along with new applications of intravascular imaging and the latest advances in computer assisted stenting. Brings together scientific researchers, medical experts, and industry partners working in different anatomical regions Presents an introduction to the clinical workflow and current challenges in endovascular Interventions Provides a review of the state-of-the-art methodologies in endovascular imaging and their applications Poses outstanding questions and discusses future research

Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting

Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting Book
Author : Simone Balocco,Maria A. Zuluaga,Guillaume Zahnd,Stefanie Demirci,Su-Lin Lee
Publisher : Academic Press
Release : 2016-12-01
ISBN : 9780128110188
Language : En, Es, Fr & De

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Book Description :

Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting presents imaging, treatment, and computed assisted technological techniques for diagnostic and intraoperative vascular imaging and stenting. These techniques offer increasingly useful information on vascular anatomy and function, and are poised to have a dramatic impact on the diagnosis, analysis, modeling, and treatment of vascular diseases. After setting out the technical and clinical challenges of vascular imaging and stenting, the book gives a concise overview of the basics before presenting state-of-the-art methods for solving these challenges. Readers will learn about the main challenges in endovascular procedures, along with new applications of intravascular imaging and the latest advances in computer assisted stenting. Brings together scientific researchers, medical experts, and industry partners working in different anatomical regions Presents an introduction to the clinical workflow and current challenges in endovascular Interventions Provides a review of the state-of-the-art methodologies in endovascular imaging and their applications Poses outstanding questions and discusses future research

Intravascular Imaging and Computer Assisted Stenting and Large Scale Annotation of Biomedical Data and Expert Label Synthesis

Intravascular Imaging and Computer Assisted Stenting  and Large Scale Annotation of Biomedical Data and Expert Label Synthesis Book
Author : M. Jorge Cardoso,Tal Arbel,Su-Lin Lee,Veronika Cheplygina,Simone Balocco,Diana Mateus,Guillaume Zahnd,Lena Maier-Hein,Stefanie Demirci,Eric Granger,Luc Duong,Marc-André Carbonneau,Shadi Albarqouni,Gustavo Carneiro
Publisher : Springer
Release : 2017-09-06
ISBN : 3319675346
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed joint proceedings of the 6th Joint International Workshop on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2017, and the Second International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017. The 6 full papers presented at CVII-STENT 2017 and the 11 full papers presented at LABELS 2017 were carefully reviewed and selected. The CVII-STENT papers feature the state of the art in imaging, treatment, and computer-assisted intervention in the field of endovascular interventions. The LABELS papers present a variety of approaches for dealing with few labels, from transfer learning to crowdsourcing.

Intravascular Imaging and Computer Assisted Stenting and Large Scale Annotation of Biomedical Data and Expert Label Synthesis

Intravascular Imaging and Computer Assisted Stenting and Large Scale Annotation of Biomedical Data and Expert Label Synthesis Book
Author : Danail Stoyanov,Zeike Taylor,Simone Balocco,Raphael Sznitman,Anne Martel,Lena Maier-Hein,Luc Duong,Guillaume Zahnd,Stefanie Demirci,Shadi Albarqouni,Su-Lin Lee,Stefano Moriconi,Veronika Cheplygina,Diana Mateus,Emanuele Trucco,Eric Granger,Pierre Jannin
Publisher : Springer
Release : 2018-10-16
ISBN : 3030013642
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed joint proceedings of the 7th Joint International Workshop on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2018, and the Third International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2018, held in conjunction with the 21th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 9 full papers presented at CVII-STENT 2017 and the 12 full papers presented at LABELS 2017 were carefully reviewed and selected. The CVII-STENT papers feature the state of the art in imaging, treatment, and computer-assisted intervention in the field of endovascular interventions. The LABELS papers present a variety of approaches for dealing with few labels, from transfer learning to crowdsourcing.

Machine Learning and Medical Engineering for Cardiovascular Health and Intravascular Imaging and Computer Assisted Stenting

Machine Learning and Medical Engineering for Cardiovascular Health and Intravascular Imaging and Computer Assisted Stenting Book
Author : Hongen Liao,Simone Balocco,Guijin Wang,Feng Zhang,Yongpan Liu,Zijian Ding,Luc Duong,Renzo Phellan,Guillaume Zahnd,Katharina Breininger,Shadi Albarqouni,Stefano Moriconi,Su-Lin Lee,Stefanie Demirci
Publisher : Springer Nature
Release : 2019-10-12
ISBN : 3030333272
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed proceedings of the First International Workshop on Machine Learning and Medical Engineering for Cardiovasvular Healthcare, MLMECH 2019, and the International Joint Workshops on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. For MLMECH 2019, 16 papers were accepted for publication from a total of 21 submissions. They focus on machine learning techniques and analyzing of ECG data in the diagnosis of heart diseases. CVII-STENT 2019 accepted all 8 submissiones for publication. They contain technological and scientific research concerning endovascular procedures.

Handbook of Medical Image Computing and Computer Assisted Intervention

Handbook of Medical Image Computing and Computer Assisted Intervention Book
Author : Kevin Zhou,Daniel Rueckert,Gabor Fichtinger
Publisher : Academic Press
Release : 2019-10-18
ISBN : 0128165863
Language : En, Es, Fr & De

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Book Description :

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

Intravascular Ultrasound

Intravascular Ultrasound Book
Author : Balocco Simone
Publisher : Elsevier
Release : 2020-06-06
ISBN : 0128188340
Language : En, Es, Fr & De

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Book Description :

Intravascular Ultrasound: From Acquisition to Advanced Quantitative Analysis covers topics of the whole imaging pipeline, ranging from the definition of the clinical problem and image acquisition systems to image processing and analysis, including the assisted clinical-decision making procedures and treatment planning (stent deployment and follow up). Atherosclerosis, a disease of the vessel wall that produces vessel narrowing and obstruction, is the major cause of cardiovascular diseases, such as heart attack or stroke. This book covers all aspects of this imaging tool that allows for the visualization of internal vessel structures and the quantification and characterization of coronary plaque. Provides an introduction to the clinical workflow and current challenges in endovascular interventions Presents a review of the state-of-the-art methodologies in IVUS imaging and their applications Includes a rich analysis of the current and potential future connections between the academic, clinical and industrial fields

Deep Network Design for Medical Image Computing

Deep Network Design for Medical Image Computing Book
Author : Haofu Liao,S. Kevin Zhou,Jiebo Luo
Publisher : Academic Press
Release : 2022-09-01
ISBN : 0128244038
Language : En, Es, Fr & De

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Book Description :

Deep Network Design for Medical Image Computing: Principles and Applications covers a range of MIC tasks and discusses design principles of these tasks for deep learning approaches in medicine. These include skin disease classification, vertebrae identification and localization, cardiac ultrasound image segmentation, 2D/3D medical image registration for intervention, metal artifact reduction, sparse-view artifact reduction, etc. For each topic, the book provides a deep learning-based solution that takes into account the medical or biological aspect of the problem and how the solution addresses a variety of important questions surrounding architecture, the design of deep learning techniques, when to introduce adversarial learning, and more. This book will help graduate students and researchers develop a better understanding of the deep learning design principles for MIC and to apply them to their medical problems. Explains design principles of deep learning techniques for MIC Contains cutting-edge deep learning research on MIC Covers a broad range of MIC tasks, including the classification, detection, segmentation, registration, reconstruction and synthesis of medical images

Computational Retinal Image Analysis

Computational Retinal Image Analysis Book
Author : Emanuele Trucco,Tom MacGillivray,Yanwu Xu
Publisher : Academic Press
Release : 2019-11-25
ISBN : 0081028172
Language : En, Es, Fr & De

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Book Description :

Computational Retinal Image Analysis: Tools, Applications and Perspectives gives an overview of contemporary retinal image analysis (RIA) in the context of healthcare informatics and artificial intelligence. Specifically, it provides a history of the field, the clinical motivation for RIA, technical foundations (image acquisition modalities, instruments), computational techniques for essential operations, lesion detection (e.g. optic disc in glaucoma, microaneurysms in diabetes) and validation, as well as insights into current investigations drawing from artificial intelligence and big data. This comprehensive reference is ideal for researchers and graduate students in retinal image analysis, computational ophthalmology, artificial intelligence, biomedical engineering, health informatics, and more. Provides a unique, well-structured and integrated overview of retinal image analysis Gives insights into future areas, such as large-scale screening programs, precision medicine, and computer-assisted eye care Includes plans and aspirations of companies and professional bodies

Biomedical Image Synthesis and Simulation

Biomedical Image Synthesis and Simulation Book
Author : Ninon Burgos,David Svoboda
Publisher : Academic Press
Release : 2022-06-30
ISBN : 0128243503
Language : En, Es, Fr & De

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Book Description :

Biomedical Image Synthesis and Simulations: Methods and Applications presents the latest on basic concepts and applications in image-based simulation and synthesis used in medical and biomedical imaging. Sections introduce and describe the simulation and synthesis methods that were developed and successfully used within the last twenty years and give examples of successful applications of these methods. As the book provides a survey of all the commonly established approaches and more recent deep learning methods, it is highly suitable for graduate students and researchers in medical and biomedical imaging. Gives state-of-the-art methods in (bio)medical image synthesis Explains the principles (background) of image synthesis methods Presents the main applications of biomedical image synthesis methods

Meta Learning

Meta Learning Book
Author : Lan Zou
Publisher : Elsevier
Release : 2022-11-18
ISBN : 0323903703
Language : En, Es, Fr & De

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Book Description :

Deep neural networks (DNNs) with their dense and complex algorithms provide real possibilities for Artificial General Intelligence (AGI). Meta-learning with DNNs brings AGI much closer: artificial agents solving intelligent tasks that human beings can achieve, even transcending what they can achieve. Meta-Learning: Theory, Algorithms and Applications shows how meta-learning in combination with DNNs advances towards AGI. The book explains the fundamentals of meta-learning by providing answers to these questions: What is meta-learning?; why do we need meta-learning?; how are self-improved meta-learning mechanisms heading for AGI ?; how can we use meta-learning in our approach to specific scenarios? The book presents the background of seven mainstream paradigms: meta-learning, few-shot learning, deep learning, transfer learning, machine learning, probabilistic modeling, and Bayesian inference. It then explains important state-of-the-art mechanisms and their variants for meta-learning, including memory-augmented neural networks, meta-networks, convolutional Siamese neural networks, matching networks, prototypical networks, relation networks, LSTM meta-learning, model-agnostic meta-learning, and the Reptile algorithm. The book takes a deep dive into nearly 200 state-of-the-art meta-learning algorithms from top tier conferences (e.g. NeurIPS, ICML, CVPR, ACL, ICLR, KDD). It systematically investigates 39 categories of tasks from 11 real-world application fields: Computer Vision, Natural Language Processing, Meta-Reinforcement Learning, Healthcare, Finance and Economy, Construction Materials, Graphic Neural Networks, Program Synthesis, Smart City, Recommended Systems, and Climate Science. Each application field concludes by looking at future trends or by giving a summary of available resources Meta-Learning: Theory, Algorithms and Applications is a great resource to understand the principles of meta-learning and to learn state-of-the-art meta-learning algorithms, giving the student, researcher and industry professional the ability to apply meta-learning for various novel applications. • A comprehensive overview of state-of-the-art meta-learning techniques and methods associated with deep neural networks together with a broad range of application areas • Coverage of nearly 200 state-of-the-art meta-learning algorithms, which are promoted by premier global AI conferences and journals, and 300 to 450 pieces of key research. • Systematic and detailed exploration of the most crucial state-of-the-art meta-learning algorithm mechanisms: model-based, metric-based, and optimization-based. • Provides solutions to the limitations of using deep learning and/or machine learning methods, particularly with small sample sizes and unlabeled data • Gives an understanding of how meta-learning acts as a stepping stone to Artificial General Intelligence in 39 categories of tasks from 11 real-world application fields.

Riemannian Geometric Statistics in Medical Image Analysis

Riemannian Geometric Statistics in Medical Image Analysis Book
Author : Xavier Pennec,Stefan Sommer,Tom Fletcher
Publisher : Academic Press
Release : 2019-09
ISBN : 0128147253
Language : En, Es, Fr & De

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Book Description :

Over the past 15 years, there has been a growing need in the medical image computing community for principled methods to process nonlinear geometric data. Riemannian geometry has emerged as one of the most powerful mathematical and computational frameworks for analyzing such data. Riemannian Geometric Statistics in Medical Image Analysis is a complete reference on statistics on Riemannian manifolds and more general nonlinear spaces with applications in medical image analysis. It provides an introduction to the core methodology followed by a presentation of state-of-the-art methods. Content includes: - The foundations of Riemannian geometric methods for statistics on manifolds with emphasis on concepts rather than on proofs - Applications of statistics on manifolds and shape spaces in medical image computing - Diffeomorphic deformations and their applications As the methods described apply to domains such as signal processing (radar signal processing and brain computer interaction), computer vision (object and face recognition), and other domains where statistics of geometric features appear, this book is suitable for researchers and graduate students in medical imaging, engineering and computer science. - A complete reference covering both the foundations and state-of-the-art methods - Edited and authored by leading researchers in the field - Contains theory, examples, applications, and algorithms - Gives an overview of current research challenges and future applications

Radiomics and Its Clinical Application

Radiomics and Its Clinical Application Book
Author : Jie Tian,Di Dong,Zhenyu Liu,Jingwei Wei
Publisher : Academic Press
Release : 2021-06-03
ISBN : 0128181028
Language : En, Es, Fr & De

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Book Description :

The rapid development of artificial intelligence technology in medical data analysis has led to the concept of radiomics. This book introduces the essential and latest technologies in radiomics, such as imaging segmentation, quantitative imaging feature extraction, and machine learning methods for model construction and performance evaluation, providing invaluable guidance for the researcher entering the field. It fully describes three key aspects of radiomic clinical practice: precision diagnosis, the therapeutic effect, and prognostic evaluation, which make radiomics a powerful tool in the clinical setting. This book is a very useful resource for scientists and computer engineers in machine learning and medical image analysis, scientists focusing on antineoplastic drugs, and radiologists, pathologists, oncologists, as well as surgeons wanting to understand radiomics and its potential in clinical practice. An introduction to the concepts of radiomics In-depth presentation of the core technologies and methods Summary of current radiomics research, perspective on the future of radiomics and the challenges ahead An introduction to several platforms that are planned to be built: cooperation, data sharing, software, and application platforms

Intelligent Healthcare

Intelligent Healthcare Book
Author : Chinmay Chakraborty
Publisher : Springer Nature
Release : 2022
ISBN : 9811681503
Language : En, Es, Fr & De

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Book Description :

The book Intelligent Healthcare: Infrastructure, Algorithms, and Management® cover a wide range of research topics on innovative intelligent healthcare solutions and advancements with the latest research developments. Data analytics are relevant for healthcare to meet many technical challenges and issues that need to be addressed to realize this potential. The advanced healthcare systems have to be upgraded with new capabilities such as data analytics, machine learning, intelligent decision making, and more professional services. The Internet of Things helps to design and develop intelligent healthcare solutions assisted by security, data analytics, and machine learning. This book will provide federated learning, Data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart healthcare. This book aims to attract works on multidisciplinary research spanning across computer science and engineering, environmental studies, services, urban planning and development, Healthcare, social sciences, and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative learning and computing solutions and big medical data-powered applications to cope with the real-world challenges for building smart healthcare sectors. Main Features: Ø Immersive technologies in healthcare Ø Internet of medical things Ø Federated learning algorithms Ø Explainable AI in Pervasive Healthcare Ø New management principles using biomedical data Ø Secured healthcare management systems This book aims to set up a better understanding of data scientists, researchers, and technologists under innovative digital health. The reader can find out existing research challenges, current market trends, and low-cost technologies to smoothly address the digital health issue.

Biomedical Texture Analysis

Biomedical Texture Analysis Book
Author : Adrien Depeursinge,Omar S Al-Kadi,J.Ross Mitchell
Publisher : Academic Press
Release : 2017-08-25
ISBN : 0128123214
Language : En, Es, Fr & De

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Book Description :

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

Rutherford s Vascular Surgery and Endovascular Therapy 2 Volume Set E Book

Rutherford s Vascular Surgery and Endovascular Therapy  2 Volume Set E Book Book
Author : Anton P Sidawy,Bruce A Perler
Publisher : Elsevier Health Sciences
Release : 2022-06-04
ISBN : 0323775608
Language : En, Es, Fr & De

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Book Description :

Encyclopedic, definitive, and state-of-the-art in the field of vascular disease and its medical, surgical, and interventional management, Rutherford's Vascular Surgery and Endovascular Therapy offers authoritative guidance from the most respected and innovative global thought leaders and clinical and basic science experts of our time. The thoroughly revised 10th Edition, published in association with the Society for Vascular Surgery and authored by multidisciplinary and international contributors, is an outstanding reference for vascular surgeons, vascular medicine specialists, interventional radiologists and cardiologists, and their trainees who depend upon Rutherford’s in their practice. Under the expert editorial guidance of Drs. Anton N. Sidawy and Bruce A. Perler, it is quite simply the most complete and most reliable resource available on the art and science of circulatory diseases. Incorporates fundamental vascular biology, diagnostic techniques, and decision making as well as medical, endovascular, and surgical treatment of vascular disease. Features numerous concise and comprehensive diagnostic and therapeutic algorithms vital to patient evaluation and management. Covers all vascular imaging techniques, offering a non-invasive evaluation of both the morphology and hemodynamics of the vascular system. Employs a full-color layout, images and online videos, so readers can view clinical and physical findings and operative techniques more vividly. Contains fully updated and more concise chapters with a focused format and summary for each that provides a quick access to key information—ideal for consultation as well as daily practice. Includes expanded coverage of the business of vascular surgery, including a new section on the use of technology platforms and social media, and new chapters on telemedicine, the development and operation of outpatient dialysis centers and multispecialty cardiovascular centers, vascular information on the internet, and much more. Provides new content on key topics such as endovascular treatment of complex aortic disease, acute vascular occlusion in the pediatric population, outpatient vascular care, and anatomic surgical exposures for open surgical reconstructions.

Deep Learning for Medical Image Analysis

Deep Learning for Medical Image Analysis Book
Author : S. Kevin Zhou,Hayit Greenspan,Dinggang Shen
Publisher : Academic Press
Release : 2017-01-18
ISBN : 0128104090
Language : En, Es, Fr & De

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Book Description :

Deep learning is providing exciting solutions for medical image analysis problems and is seen as 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 have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research problems in medical image analysis and their challenges Describes 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 Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache

Pattern Recognition

Pattern Recognition Book
Author : Michael Cree,Fay Huang,Junsong Yuan,Wei Qi Yan
Publisher : Springer Nature
Release : 2020-03-06
ISBN : 9811536511
Language : En, Es, Fr & De

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Book Description :

This volume constitutes the refereed proceedings, presented during the ACPR 2019 Workshops, held in Auckland, New Zealand, in November 2019. The 17 full papers and 6 short papers were carefully reviewed and selected out of numerous submissions. The papers are organized according to the topics of the workshops: computer vision for modern vehicles; advances and applications on generative deep learning models; image and pattern analysis for multidisciplinary computational anatomy; multi-sensor for action and gesture recognition; towards the automatic data processing chain for airborne and spaceborne sensors.

Computational Intelligence And Image Processing In Medical Applications

Computational Intelligence And Image Processing In Medical Applications Book
Author : Chi Hau Chen
Publisher : World Scientific
Release : 2022-05-30
ISBN : 9811257469
Language : En, Es, Fr & De

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Book Description :

In recent years, there have been significant progress in computational intelligence and image processing with machine learning and deep learning as important components of modern artificial intelligence. All these progresses face challenges in dealing with Covid-19 pandemic for detection and treatment.This comprehensive compendium provides not only updated advances of computational intelligence and image processing in the detection and treatment of Covid-19, but also other medical applications such as in cancer detection and cardiovascular diseases, etc. More traditional approaches such as 2D segmentation and 3D reconstruction are included.The useful reference text is an updated version of the edited title, Computer Vision in Medical Imaging (World Scientific, 2014) and its companion volume, Frontiers of Medical Imaging (World Scientific, 2015). The book is written for engineers, scientists and the medical community to meet the increased challenges in medical applications.

Intravascular Imaging and Computer Assisted Stenting and Large Scale Annotation of Biomedical Data and Expert Label Synthesis

Intravascular Imaging and Computer Assisted Stenting  and Large Scale Annotation of Biomedical Data and Expert Label Synthesis Book
Author : M. Jorge Cardoso,Tal Arbel,Su-Lin Lee,Veronika Cheplygina,Simone Balocco,Diana Mateus,Guillaume Zahnd,Lena Maier-Hein,Stefanie Demirci,Eric Granger,Luc Duong,Marc-André Carbonneau,Shadi Albarqouni,Gustavo Carneiro
Publisher : Springer
Release : 2017-09-08
ISBN : 9783319675336
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed joint proceedings of the 6th Joint International Workshop on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2017, and the Second International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017. The 6 full papers presented at CVII-STENT 2017 and the 11 full papers presented at LABELS 2017 were carefully reviewed and selected. The CVII-STENT papers feature the state of the art in imaging, treatment, and computer-assisted intervention in the field of endovascular interventions. The LABELS papers present a variety of approaches for dealing with few labels, from transfer learning to crowdsourcing.