Deep learning for medical image analysis / edited by Kevin Zhou, Hayit Greenspan, Dinggang Shen.

Format:

Book

Author/Creator:

Zhou, S., author.

Contributor:

Zhou, S. Kevin, editor.

Greenspan, Hayit, editor.

Shen, Dinggang, editor.

Language:

English

Subjects (All):

Diagnostic imaging--Data processing.

Diagnostic imaging.

Image analysis.

Physical Description:

1 online resource (460 pages) : illustrations, photographs

Edition:

First edition.

Place of Publication:

London, England : Academic Press, 2017.

System Details:

text file

Summary:

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. Covers common research problems in medical image analysis and their challenges Describes 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 Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache

Contents:

Introduction

Medical Image Detection and recognition

Medical image segmentation

Medical image registration

Computer-aided diagnosis and disease quantification

Others.

Notes:

Includes bibliographical references at the end of each chapters and index.

Description based on print version record.

ISBN:

9780128104095

0128104090

9780128104088

0128104082

OCLC:

976000729