This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of- the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image. Written by top experts in Medical Imaging, this book is ideal for university researchers and industry practitioners in medical imaging who want a complete reference on key methods, algorithms and applications in medical image recognition, segmentation and parsing of multiple objects. Learn:- Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects- Methods and theories for medical image recognition, segmentation and parsing of multiple objects- Efficient and effective machine learning solutions based on big datasets- Selected applications of medical image parsing using proven algorithms- Provides a comprehensive overview of state-of-the-art research on medical image recognition, segmentation, and parsing of multiple objects- Presents efficient and effective approaches based on machine learning paradigms to leverage the anatomical context in the medical images, best exemplified by large datasets- Includes algorithms for recognizing and parsing of known anatomies for practical applications
S. Kevin Zhou
Medical Image Recognition, Segmentation and Parsing [EPUB ebook]
Machine Learning and Multiple Object Approaches
Medical Image Recognition, Segmentation and Parsing [EPUB ebook]
Machine Learning and Multiple Object Approaches
购买此电子书可免费获赠一本!
语言 英语 ● 格式 EPUB ● ISBN 9780128026762 ● 出版者 Elsevier Science ● 发布时间 2015 ● 下载 3 时 ● 货币 EUR ● ID 4818275 ● 复制保护 Adobe DRM
需要具备DRM功能的电子书阅读器