Hybrid Machine Intelligence for Medical Image Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Hybrid Machine Intelligence for Medical Image Analysis write by Siddhartha Bhattacharyya. This book was released on 2019-08-08. Hybrid Machine Intelligence for Medical Image Analysis available in PDF, EPUB and Kindle. The book discusses the impact of machine learning and computational intelligent algorithms on medical image data processing, and introduces the latest trends in machine learning technologies and computational intelligence for intelligent medical image analysis. The topics covered include automated region of interest detection of magnetic resonance images based on center of gravity; brain tumor detection through low-level features detection; automatic MRI image segmentation for brain tumor detection using the multi-level sigmoid activation function; and computer-aided detection of mammographic lesions using convolutional neural networks.
Advanced Machine Vision Paradigms for Medical Image Analysis
Advanced Machine Vision Paradigms for Medical Image Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Advanced Machine Vision Paradigms for Medical Image Analysis write by Tapan K. Gandhi. This book was released on 2020-08-11. Advanced Machine Vision Paradigms for Medical Image Analysis available in PDF, EPUB and Kindle. Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis
Hybrid Image Processing Methods for Medical Image Examination
Hybrid Image Processing Methods for Medical Image Examination - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Hybrid Image Processing Methods for Medical Image Examination write by Venkatesan Rajinikanth. This book was released on 2021-01-29. Hybrid Image Processing Methods for Medical Image Examination available in PDF, EPUB and Kindle. In view of better results expected from examination of medical datasets (images) with hybrid (integration of thresholding and segmentation) image processing methods, this work focuses on implementation of possible hybrid image examination techniques for medical images. It describes various image thresholding and segmentation methods which are essential for the development of such a hybrid processing tool. Further, this book presents the essential details, such as test image preparation, implementation of a chosen thresholding operation, evaluation of threshold image, and implementation of segmentation procedure and its evaluation, supported by pertinent case studies. Aimed at researchers/graduate students in the medical image processing domain, image processing, and computer engineering, this book: Provides broad background on various image thresholding and segmentation techniques Discusses information on various assessment metrics and the confusion matrix Proposes integration of the thresholding technique with the bio-inspired algorithms Explores case studies including MRI, CT, dermoscopy, and ultrasound images Includes separate chapters on machine learning and deep learning for medical image processing
Hybrid Intelligence for Image Analysis and Understanding
Hybrid Intelligence for Image Analysis and Understanding - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Hybrid Intelligence for Image Analysis and Understanding write by Siddhartha Bhattacharyya. This book was released on 2017-07-27. Hybrid Intelligence for Image Analysis and Understanding available in PDF, EPUB and Kindle. A synergy of techniques on hybrid intelligence for real-life image analysis Hybrid Intelligence for Image Analysis and Understanding brings together research on the latest results and progress in the development of hybrid intelligent techniques for faithful image analysis and understanding. As such, the focus is on the methods of computational intelligence, with an emphasis on hybrid intelligent methods applied to image analysis and understanding. The book offers a diverse range of hybrid intelligence techniques under the umbrellas of image thresholding, image segmentation, image analysis and video analysis. Key features: Provides in-depth analysis of hybrid intelligent paradigms. Divided into self-contained chapters. Provides ample case studies, illustrations and photographs of real-life examples to illustrate findings and applications of different hybrid intelligent paradigms. Offers new solutions to recent problems in computer science, specifically in the application of hybrid intelligent techniques for image analysis and understanding, using well-known contemporary algorithms. The book is essential reading for lecturers, researchers and graduate students in electrical engineering and computer science.
Deep Learning for Medical Image Analysis
Deep Learning for Medical Image Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Deep Learning for Medical Image Analysis write by S. Kevin Zhou. This book was released on 2023-12-01. Deep Learning for Medical Image Analysis available in PDF, EPUB and Kindle. 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
