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Computational Pathology And Ophthalmic Medical Image Analysis
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Book Synopsis Computational Pathology and Ophthalmic Medical Image Analysis by : Danail Stoyanov
Download or read book Computational Pathology and Ophthalmic Medical Image Analysis written by Danail Stoyanov and published by Springer. This book was released on 2018-09-13 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the First International Workshop on Computational Pathology, COMPAY 2018, and the 5th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 19 full papers (out of 25 submissions) presented at COMPAY 2018 and the 21 full papers (out of 31 submissions) presented at OMIA 2018 were carefully reviewed and selected. The COMPAY papers focus on artificial intelligence and deep learning. The OMIA papers cover various topics in the field of ophthalmic image analysis.
Book Synopsis Computational Retinal Image Analysis by : Emanuele Trucco
Download or read book Computational Retinal Image Analysis written by Emanuele Trucco and published by Academic Press. This book was released on 2019-11-19 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Deep Learning for Medical Image Analysis by : S. Kevin Zhou
Download or read book Deep Learning for Medical Image Analysis written by S. Kevin Zhou and published by Academic Press. This book was released on 2023-11-23 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Data-Enabled Intelligence for Medical Technology Innovation, Volume I by : Nianyin Zeng
Download or read book Data-Enabled Intelligence for Medical Technology Innovation, Volume I written by Nianyin Zeng and published by Frontiers Media SA. This book was released on 2022-02-21 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Intelligence and Ophthalmology by : Parul Ichhpujani
Download or read book Artificial Intelligence and Ophthalmology written by Parul Ichhpujani and published by Springer Nature. This book was released on 2021-04-22 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book helps to explore the vast expanse of artificial intelligence-based scientific content that has been published in the last few years. Ophthalmology has recently undergone a silent digital revolution, with machine learning and deep learning algorithms consistently outperforming human graders in studies published across the globe. It is high time that a resource that breaks this information behemoth into easily digestible bits comes to the fore. This book simplifies the complex mechanics of algorithms used in ophthalmology and vision science applications. It also tries to address potential ethical issues with machines entering our clinics and patients’ lives. Overall it is essential reading for ophthalmologists/eye care professionals interested in artificial intelligence and everyone who is looking for a deep dive into the exciting world of digital medicine.
Book Synopsis Medical Imaging and Computer-Aided Diagnosis by : Ruidan Su
Download or read book Medical Imaging and Computer-Aided Diagnosis written by Ruidan Su and published by Springer Nature. This book was released on 2024-01-20 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers virtually all aspects of image formation in medical imaging, including systems based on ionizing radiation (x-rays, gamma rays) and non-ionizing techniques (ultrasound, optical, thermal, magnetic resonance, and magnetic particle imaging) alike. In addition, it discusses the development and application of computer-aided detection and diagnosis (CAD) systems in medical imaging. Given its coverage, the book provides both a forum and valuable resource for researchers involved in image formation, experimental methods, image performance, segmentation, pattern recognition, feature extraction, classifier design, machine learning / deep learning, radiomics, CAD workstation design, human–computer interaction, databases, and performance evaluation.
Book Synopsis Deep Learning for Medical Applications with Unique Data by : Deepak Gupta
Download or read book Deep Learning for Medical Applications with Unique Data written by Deepak Gupta and published by Academic Press. This book was released on 2022-02-15 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning for Medical Applications with Unique Data informs readers about the most recent deep learning-based medical applications in which only unique data gathered in real cases are used. The book provides examples of how deep learning can be used in different problem areas and frameworks in both clinical and research settings, including medical image analysis, medical image registration, time series analysis, medical data synthesis, drug discovery, and pre-processing operations. The volume discusses not only positive findings, but also negative ones obtained by deep learning techniques, including the use of newly developed deep learning techniques rarely reported in the existing literature. The book excludes research works with ready data sets and includes only unique data use to better understand the state of deep learning in real-world cases, along with the feedback and user experiences from physicians and medical staff for applied deep learning-based solutions. Other applications presented in the book include hybrid solutions with deep learning support, disease diagnosis with deep learning focusing on rare diseases and cancer, patient care and treatment, genomics research, as well as research on robotics and autonomous systems. - Introduces deep learning, demonstrating concepts for a wide variety of medical applications using unique data, excluding research with ready datasets - Encompasses a wide variety of biomedical applications, including unsupervised learning, natural language processing, pattern recognition, image and video processing and disease diagnosis - Provides a robust set of methods that will help readers appropriately and judiciously use the most suitable deep learning techniques for their applications
Book Synopsis Soft Computing and Signal Processing by : V. Sivakumar Reddy
Download or read book Soft Computing and Signal Processing written by V. Sivakumar Reddy and published by Springer Nature. This book was released on 2021-07-23 with total page 663 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected research papers on current developments in the fields of soft computing and signal processing from the Third International Conference on Soft Computing and Signal Processing (ICSCSP 2020). The book covers topics such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning and discusses various aspects of these topics, e.g., technological considerations, product implementation and application issues.
Book Synopsis Multidisciplinary Computational Anatomy by : Makoto Hashizume
Download or read book Multidisciplinary Computational Anatomy written by Makoto Hashizume and published by Springer Nature. This book was released on 2021-11-30 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume thoroughly describes the fundamentals of a new multidisciplinary field of study that aims to deepen our understanding of the human body by combining medical image processing, mathematical analysis, and artificial intelligence. Multidisciplinary Computational Anatomy (MCA) offers an advanced diagnosis and therapeutic navigation system to help detect or predict human health problems from the micro-level to macro-level using a four-dimensional, dynamic approach to human anatomy: space, time, function, and pathology. Applying this dynamic and “living” approach in the clinical setting will promote better planning for – and more accurate, effective, and safe implementation of – medical management. Multidisciplinary Computational Anatomy will appeal not only to clinicians but also to a wide readership in various scientific fields such as basic science, engineering, image processing, and biomedical engineering. All chapters were written by respected specialists and feature abundant color illustrations. Moreover, the findings presented here share new insights into unresolved issues in the diagnosis and treatment of disease, and into the healthy human body.
Book Synopsis Artificial Intelligence in Digital Pathology Image Analysis by : Min Tang
Download or read book Artificial Intelligence in Digital Pathology Image Analysis written by Min Tang and published by Frontiers Media SA. This book was released on 2024-09-25 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thanks to the development and deployment of whole-slide imaging technology in pathology, glass slides previously observed under a traditional microscope are now scanned and converted to digital images, which are more beneficial for remote access, portability, and ease of sharing to facilitate telepathology. More importantly, digitization of glass slides paves the way towards the wide use of artificial intelligence (AI) tools including machine/deep learning algorithms, resulting in improved diagnostic accuracy. In the past decade, a large number of studies have demonstrated the remarkable success of AI, particularly deep learning, in digital pathology, such as tumor region identification, metastasis detection, and patient prognosis. Differing from handcrafted feature-based approaches that take advantage of domain knowledge to delineate specific morphological measurements (e.g., nuclei shape and size and tissue texture) in the images as features for training, deep learning is a paradigm of feature learning entirely driven by the image data and/or labels. Herein, the use of deep learning in pathological diagnosis can not only handle increased workloads and expertise shortages but also obviate subjective diagnosis from pathologists. Yet there remain many scientific and technological challenges associated with the efficiency of deep learning algorithms for use in clinical practice. For example, deep learning requires a sufficient amount of training data for generalization and suffers from a lack of feature interpretability. The overarching goal of this special issue is to highlight novel research accomplishments and directions, related to advanced AI methodology development and applications in digital pathology.
Book Synopsis Deep Learning in Medical Image Analysis by : Gobert Lee
Download or read book Deep Learning in Medical Image Analysis written by Gobert Lee and published by Springer Nature. This book was released on 2020-02-06 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.
Book Synopsis Artificial Intelligence and Deep Learning in Pathology by : Stanley Cohen
Download or read book Artificial Intelligence and Deep Learning in Pathology written by Stanley Cohen and published by Elsevier Health Sciences. This book was released on 2020-06-02 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in computational algorithms, along with the advent of whole slide imaging as a platform for embedding artificial intelligence (AI), are transforming pattern recognition and image interpretation for diagnosis and prognosis. Yet most pathologists have just a passing knowledge of data mining, machine learning, and AI, and little exposure to the vast potential of these powerful new tools for medicine in general and pathology in particular. In Artificial Intelligence and Deep Learning in Pathology, Dr. Stanley Cohen covers the nuts and bolts of all aspects of machine learning, up to and including AI, bringing familiarity and understanding to pathologists at all levels of experience. - Focuses heavily on applications in medicine, especially pathology, making unfamiliar material accessible and avoiding complex mathematics whenever possible. - Covers digital pathology as a platform for primary diagnosis and augmentation via deep learning, whole slide imaging for 2D and 3D analysis, and general principles of image analysis and deep learning. - Discusses and explains recent accomplishments such as algorithms used to diagnose skin cancer from photographs, AI-based platforms developed to identify lesions of the retina, using computer vision to interpret electrocardiograms, identifying mitoses in cancer using learning algorithms vs. signal processing algorithms, and many more.
Book Synopsis Deep Learning Applications in Translational Bioinformatics by : Khalid Raza
Download or read book Deep Learning Applications in Translational Bioinformatics written by Khalid Raza and published by Elsevier. This book was released on 2024-03-07 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning Applications in Translational Bioinformatics, a new volume in the Advances in Ubiquitous Sensing Application for Healthcare series, offers a detailed overview of basic bioinformatics, deep learning, various applications of deep learning in translational bioinformatics including deep learning ensembles, deep learning in protein classification, detection of various diseases, prediction of antiviral peptides, identification of antibiotic resistance, computer aided drug design and drug formulation. This new volume helps researchers working in the field of machine learning and bioinformatics to foster future research and development in ensemble deep learning and inspire new bioinformatics applications that cannot be attained by using traditional machine learning models. - Addresses the practical application of deep learning algorithms to a wide range of bioinformatics challenges - Presents integrative and multidisciplinary approaches to ubiquitous healthcare - Includes case studies to illustrate the concepts discussed
Book Synopsis Emerging Multi-Modalities Healthcare Analytics Using Machine Learning by : Khin Wee Lai
Download or read book Emerging Multi-Modalities Healthcare Analytics Using Machine Learning written by Khin Wee Lai and published by Frontiers Media SA. This book was released on 2022-11-15 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Digital Pathology by : Constantino Carlos Reyes-Aldasoro
Download or read book Digital Pathology written by Constantino Carlos Reyes-Aldasoro and published by Springer. This book was released on 2019-07-03 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 15th European Congress on Digital Pathology, ECDP 2019, held in Warwick, UK in April 2019. The 21 full papers presented in this volume were carefully reviewed and selected from 30 submissions. The congress theme will be Accelerating Clinical Deployment, with a focus on computational pathology and leveraging the power of big data and artificial intelligence to bridge the gaps between research, development, and clinical uptake.
Book Synopsis Computational Retinal Image Analysis by : Emanuele Trucco
Download or read book Computational Retinal Image Analysis written by Emanuele Trucco and published by Academic Press. This book was released on 2019-11-20 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Computational Pathology for Precision Diagnosis, Treatment, and Prognosis of Cancer by : Jun Cheng
Download or read book Computational Pathology for Precision Diagnosis, Treatment, and Prognosis of Cancer written by Jun Cheng and published by Frontiers Media SA. This book was released on 2024-02-20 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt:
