Computer-Assisted Diagnosis: Diabetes and Cardiovascular Disease brings together multifaceted information on research and clinical applications from an academic, clinical, bioengineering and bioinformatics perspective. The editors provide a stellar, diverse list of authors to explore this interesting field. Academic researchers, bioengineers, new investigators and students interested in diabetes and heart disease need an authoritative reference to reduce the amount of time spent on source-searching so they can spend more time on actual research and clinical application. This reference accomplishes this with contributions by authors from around the world. Provides valuable information for academic clinicians, researchers, bioengineers and industry on diabetes and cardiovascular disease Discusses the impact of diabetes on cardiovascular disease Covers statistical classification techniques and risk stratification
|Author||: Juri Yanase,Evangelos Triantaphyllou|
|Publisher||: Infinite Study|
|Pages||: 51 pages|
Computer-aided diagnosis (CAD) in medicine is the result of a large amount of effort expended in the interface of medicine and computer science. As some CAD systems in medicine try to emulate the diagnostic decision-making process of medical experts, they can be considered as expert systems in medicine.
A major focus of the philosophy of medicine and, in general, of the philosophy of science has been the interplay of facts and values. Nowhere is an evaluation of this interplay more important than in the ethics of diagnosis. Traditionally, diagnosis has been understood as an epistemological activity which is concerned with facts and excludes the intrusion of values. The essays in this volume challenge this assumption. Questions of knowledge in diagnosis are intimately related to the concerns with intervention that characterize the applied science of medicine. Broad social and individual goals, as well as diverse ethical frameworks, are shown to condition both the processes and results of diagnosis. This has significant implications for bioethics, implications that have not previously been developed. With this volume, `the ethics of diagnosis' is established as an important branch of bioethics.
Digital Radiography has been ? rmly established in diagnostic radiology during the last decade. Because of the special requirements of high contrast and spatial resolution needed for roentgen mammography, it took some more time to develop digital m- mography as a routine radiological tool. Recent technological progress in detector and screen design as well as increased ex- rience with computer applications for image processing have now enabled Digital Mammography to become a mature modality that opens new perspectives for the diag- sis of breast diseases. The editors of this timely new volume Prof. Dr. U. Bick and Dr. F. Diekmann, both well-known international leaders in breast imaging, have for many years been very active in the frontiers of theoretical and translational clinical research, needed to bring digital mammography ? nally into the sphere of daily clinical radiology. I am very much indebted to the editors as well as to the other internationally rec- nized experts in the ? eld for their outstanding state of the art contributions to this v- ume. It is indeed an excellent handbook that covers in depth all aspects of Digital Mammography and thus further enriches our book series Medical Radiology. The highly informative text as well as the numerous well-chosen superb illustrations will enable certi? ed radiologists as well as radiologists in training to deepen their knowledge in modern breast imaging.
|Author||: Suzuki, Kenji|
|Publisher||: IGI Global|
|Release Date||: 2012-01-31|
|ISBN 10||: 1466600608|
|Pages||: 524 pages|
"This book provides a comprehensive overview of machine learning research and technology in medical decision-making based on medical images"--Provided by publisher.
|Author||: Qiang Li,Robert M. Nishikawa|
|Publisher||: Taylor & Francis|
|Release Date||: 2015-03-17|
|ISBN 10||: 1439871779|
|Pages||: 454 pages|
Improve the Accurate Detection and Diagnosis of Cancer and Other Diseases Despite the expansion of the CAD field in recent decades, there is currently no single book dedicated to the development and use of CAD systems. Filling this need, Computer-Aided Detection and Diagnosis in Medical Imaging covers the major technical advances and methodologies shaping the development and clinical utility of CAD systems in breast imaging, chest imaging, abdominal imaging, and other emerging applications. After a historical overview of CAD, the book is divided into four sections. The first section presents CAD technologies in breast imaging, which is the most advanced area of CAD application. The second section discusses CAD technologies in chest and abdominal imaging. The third section explores emerging CAD technologies in a wide range of imaging modalities designed to address a variety of diseases. The final section describes the current use of CAD systems in clinical practice as well as how CAD will play an important role in quantitative image biomarkers and imaging genomics research. This book brings together existing and emerging CAD approaches at a level understandable to students, CAD system developers, basic scientists, and physician scientists. Newcomers to CAD research will learn about fundamental aspects in the process of CAD system development. Developers of CAD systems will gain insight on designing new or improved CAD systems. Experienced researchers will get up-to-date information on the latest CAD technologies.
|Author||: Heinz U. Lemke,Kiyonari Inamura,C.Carl Jaffe,Roland Felix|
|Publisher||: Springer Science & Business Media|
|Release Date||: 2013-06-29|
|ISBN 10||: 3642493513|
|Pages||: 836 pages|
CAR is a symposium and exhibition covering the impact of computer and communication systems applied to radiology and other medical disciplines, which use digital imaging for diagnosis and therapy planning. CAR '93 also provides tutorials, but more emphasis is given to a broad variety of specific problems related to medical/technical issues in digital imaging. This is achieved through in-depth presentations of results of current medical imaging projects on a worldwide basis.
Diabetes and Fundus OCT brings together a stellar cast of authors who review the computer-aided diagnostic (CAD) systems developed to diagnose non-proliferative diabetic retinopathy in an automated fashion using Fundus and OCTA images. Academic researchers, bioengineers, new investigators and students interested in diabetes and retinopathy need an authoritative reference to bring this multidisciplinary field together to help reduce the amount of time spent on source-searching and instead focus on actual research and the clinical application. This reference depicts the current clinical understanding of diabetic retinopathy, along with the many scientific advances in understanding this condition. As the role of optical coherence tomography (OCT) in the assessment and management of diabetic retinopathy has become significant in understanding the vireo retinal relationships and the internal architecture of the retina, this information is more critical than ever. Includes unique information for academic clinicians, researchers and bioengineers Provides insights needed to understand the imaging modalities involved, the unmet clinical need that is being addressed, and the engineering and technical approaches applied Brings together details on the retinal vasculature in diabetics as imaged by optical coherence tomography angiography and automated detection of retinal disease
In June 1998 the Fourth International Workshop on Digital Mammography was held in Nijmegen, The Netherlands, where it was hosted by the department of Radiology of the University Hospital Nijmegen. This series of meetings was initiated at the 1993 SPIE Biomedical Image Processing Conference in San Jose, USA, where a number of sessions were entirely devoted to mammographic image analysis. At very successful subsequent workshops held in York, UK (1994) and Chicago, USA (1996), the scope of the conference was broadened, establishing a platform for presentation and discussion of new developments in digital mammog raphy. Topics that are addressed at these meetings are computer-aided diagnosis, image processing, detector development, system design, observer performance and clinical evaluation. The goal is to bring researchers from universities, breast cancer experts, and engineers together, to exchange information and present new scientific developments in this rapidly evolving field. This book contains all the scientific papers and posters presented at the work shop in Nijmegen. Contributions came from as many as 20 different countries and 190 participants attended the meeting. At a technical exhibit companies demon strated new products and work in progress. Abstracts of all papers were reviewed by members of the scientific committee. Many of the accepted papers had excellent quality, but due to limited space not all of them could be included as full papers in these proceedings. Papers that were rated high by the reviewers are included as long or short papers, others appear as extended abstracts in the last chapter.
|Author||: Anant Madabhushi,Jason Dowling,Pingkun Yan,Aaron Fenster,Purang Abolmaesumi,Nobuhiko Hata|
|Publisher||: Springer Science & Business Media|
|Release Date||: 2010-09-03|
|ISBN 10||: 3642159885|
|Pages||: 146 pages|
This book constitutes the refereed proceedings of the International Workshop on Prostate Cancer Imaging, held in conjunction with MICCAI 2010, in Beijing, China, in September 2010. The 11 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 13 submissions. The papers cover the clinical areas radiology, radiation oncology, digital pathology, and image guided intervention, addressing topics such as prostate segmentation, multi-modal prostate registration, computer-aided diagnosis and classification of prostate cancer.
|Author||: Ernest C. Wong|
|Release Date||: 1988|
|Pages||: 116 pages|
Diabetes and Retinopathy brings together the multifaceted information about the research and clinical application from academic, clinical, bioengineering and bioinformatics perspectives. The editors bring together a stellar cast of authors to pull together this diverse and interesting field. Academic researchers, bioengineers, new investigators and students interested in diabetes and retinopathy need an authoritative reference to bring this multidisciplinary field together to reduce the amount of time spent on source-searching and more time on actual research and the clinical application. This reference depicts the current clinical understanding of DR as well as the many scientific advances in understanding this condition. Provides valuable information for academic clinicians, researchers, bioengineers and industry on diabetes and retinopathy Discusses the impact of diabetic retinopathy, a major cause of new-onset visual loss in all the industrialized nations Covers statistical classification techniques and risk stratification
|Author||: Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi|
|Publisher||: Academic Press|
|Release Date||: 2018-11-30|
|ISBN 10||: 012816087X|
|Pages||: 345 pages|
Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers. Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains
|Author||: Kenji Suzuki,Yisong Chen|
|Release Date||: 2018-01-09|
|ISBN 10||: 331968843X|
|Pages||: 387 pages|
This book offers the first comprehensive overview of artificial intelligence (AI) technologies in decision support systems for diagnosis based on medical images, presenting cutting-edge insights from thirteen leading research groups around the world. Medical imaging offers essential information on patients’ medical condition, and clues to causes of their symptoms and diseases. Modern imaging modalities, however, also produce a large number of images that physicians have to accurately interpret. This can lead to an “information overload” for physicians, and can complicate their decision-making. As such, intelligent decision support systems have become a vital element in medical-image-based diagnosis and treatment. Presenting extensive information on this growing field of AI, the book offers a valuable reference guide for professors, students, researchers and professionals who want to learn about the most recent developments and advances in the field.
Hardbound. Over the last decade or so, many investigators have carried out basic studies and clinical applications toward the development of modern computerized schemes for detection and characterization of lesions in radiologic images, based on computer vision and artificial intelligence. These methods and techniques are generally called computer-aided diagnosis (CAD) schemes. The development of CAD has now reached a new phase, since the first commercial unit of detection of breast lesion in mammograms was approved in June 1998 by the FDA for marketing and sale for clinical use.This book, Computer-Aided Diagnosis in Medical Imaging, presents papers from the First International Workshop on Computer-Aided Diagnosis held on September, 1998 at the University of Chicago Downtown Center. The meeting provided a forum for leading researchers and practitioners in this rapidly expanding field, encompassing automated image analysis, quantitation of im
Computer technology has impacted the practice of medicine in dramatic ways. Imaging techniques provide noninvasive tools which alter the diag nostic process. Sophisticated monitoring equipment presents new levels of detail for both patient management and research. In most of these high technology applications, the computer is embedded in the device; its presence is transparent to the user. There is also a growing number of applications in which the health care provider directly interacts with a computer. In many cases, these appli cations are limited to administrative functions, e.g., office practice man agement, location of hospital patients, appointments, and scheduling. Nevertheless, there also are instances of patient care functions such as results reporting, decision support, surveillance, and reminders. This series, Computers and Medicine, will focus upon the direct use of information systems as it relates to the medical community. After twenty-five years of experimentation and experience, there are many tested applications which can be implemented economically using the current generation of computers. Moreover, the falling cost of computers suggests that there will be even more extensive use in the near future. Yet there is a gap between current practice and the state-of-the-art.
This book constitutes the refereed proceedings of the 4th International Conference on Technology Trends, CITT 2018, held in Babahoyo, Ecuador, in August 2018. The 53 revised full papers presented were carefully reviewed and selected from 204 submissions. The papers are organized in topical sections on communications; security and privacy; computer and software engineering; computational intelligence; e-government and e-participation.
"CAR" is a symposium and exhibition covering the impact of computer and communication systems applied to radiology, image-guided therapy and other medical disciplines, which use digital imaging for diagnosis and therapy planning. "CAR '95" also provides tutorials, but more emphasis is given to a broad variety of specific problems related to medical/technical issues in digital imaging. This is achieved through in-depth presentations of results of current medical imaging projects on a worldwide basis.
This book on classification in biomedical image applications presents original and valuable research work on advances in this field, which covers the taxonomy of both supervised and unsupervised models, standards, algorithms, applications and challenges. Further, the book highlights recent scientific research on artificial neural networks in biomedical applications, addressing the fundamentals of artificial neural networks, support vector machines and other advanced classifiers, as well as their design and optimization. In addition to exploring recent endeavours in the multidisciplinary domain of sensors, the book introduces readers to basic definitions and features, signal filters and processing, biomedical sensors and automation of biomeasurement systems. The target audience includes researchers and students at engineering and medical schools, researchers and engineers in the biomedical industry, medical doctors and healthcare professionals.