Medical Image Recognition, Segmentation and Parsing
Machine Learning and Multiple Object Approaches
Published on 2. December 2015
Book
Hardback
542 pages
978-0-12-802581-9 (ISBN)
Description
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
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
More details
Series
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
Professional and scholarly
Industry practitioners and university researchers in medical imaging.
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 235 mm
Width: 188 mm
Thickness: 31 mm
Weight
1218 gr
ISBN-13
978-0-12-802581-9 (9780128025819)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
S. Kevin Zhou
Medical Image Recognition, Segmentation and Parsing
Machine Learning and Multiple Object Approaches
E-Book
12/2015
Academic Press
€104.00
Available for download
Person
S. Kevin Zhou, PhD is dedicated to research on medical image computing, especially analysis and reconstruction, and its applications in real practices. Currently, he is a Distinguished Professor and Founding Executive Dean of School of Biomedical Engineering, University of Science and Technology of China (USTC) and directs the Center for Medical Imaging, Robotics, Analytic Computing and Learning (MIRACLE). Dr. Zhou was a Principal Expert and a Senior R&D Director at Siemens Healthcare Research. He has been elected as a fellow of AIMBE, IAMBE, IEEE, MICCAI and NAI and serves the MICCAI society as a board member and treasurer..
Content
PrefaceChapter 1 Introduction to Medical Image Recognition and ParsingChapter 2 Discriminative Anatomy Detection: Classification vs. RegressionChapter 3: Information Theoretic Landmark DetectionChapter 4: Submodular Landmark DetectionChapter 5: Random Forests for Anatomy Recognition Chapter 6: Integrated Detection Network for Multiple Object RecognitionChapter 7: Optimal Graph-Based Method for Multi-Object Segmentation Chapter 8: Parsing of Multiple Organs Using Learning Method and Level SetsChapter 9: Context Integration for Rapid Multiple Organ ParsingChapter 10: Multi-Atlas Methods and Label FusionChapter 11: Multi-Compartment Segmentation Framework Chapter 12: Deformable Segmentation via Sparse Representation and Dictionary Learning Chapter 13: Simultaneous Nonrigid Registration, Segmentation, and Tumor Detection Chapter 14: Whole Brain Anatomical Structure Parsing Chapter 15: Aortic and Mitral Valve Segmentation Chapter 16: Parsing of Heart, Chambers and Coronary Vessels Chapter 17: Spine Segmentation Chapter 18: Parsing of Rib and Knee BonesChapter 19: Lymph Node Segmentation Chapter 20: Polyp Segmentation from CT Colonoscopy