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
Explore Medical Image Recognition, Segmentation and Parsing by S. Kevin Zhou on eBooksStore by Arnlweb. Discover book details, reader ratings, reviews, release information, genres, and related digital books available through the iTunes Store.
This book is part of our growing collection of bestselling eBooks, popular digital reading materials, and trending author releases. Readers can explore similar books, discover new authors, and browse related genres including fiction, romance, mystery, fantasy, business, self-help, educational books, and more.
Our platform helps readers discover highly rated digital books optimized for smartphones, tablets, laptops, and desktop devices. Browse fast-loading book pages, reader reviews, and popular recommendations from bestselling authors worldwide.