edited by S. Kevin Zhou, Hayit Greenspan, Dinggang Shen.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
San Diego :
Name of Publisher, Distributor, etc.
Elsevier,
Date of Publication, Distribution, etc.
2017.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
online resource (xxiii, 433 p.) :
Other Physical Details
ill. (some col.) ;
SERIES
Series Title
Elsevier and MICCAI Society book series
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references and index.
CONTENTS NOTE
Text of Note
Introduction -- Medical Image Detection and recognition -- Medical image segmentation -- Medical image registration -- Computer-aided diagnosis and disease quantification -- Others.
0
SUMMARY OR ABSTRACT
Text of Note
"Deep learning is providing exciting solutions for medical image analysis problems and is seen as 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 have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis"--
TYPE OF ELECTRONIC RESOURCE NOTE
Text of Note
pdf file.
TOPICAL NAME USED AS SUBJECT
Entry Element
Diagnostic imaging
Entry Element
Image processing.
Entry Element
Diagnostic Imaging.
Topical Subdivision
Data processing.
DEWEY DECIMAL CLASSIFICATION
Edition
23
LIBRARY OF CONGRESS CLASSIFICATION
Class number
RC78
.
7
PERSONAL NAME - SECONDARY RESPONSIBILITY
Entry Element
Zhou, S. Kevin,
Entry Element
Greenspan, Hayit,
Entry Element
Shen, Dinggang,
ORIGINATING SOURCE
Country
Iran
Agency
University of Tehran. Library of College of Engineering (Number 2)