Deep Learning and Convolutional Neural Networks for Medical Image Computing - Precision Medicine, High Performance and Large-Scale Datasets (Hardcover, 1st ed. 2017)

This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Advances in Computer Vision and Pattern Recognition
Release date:	July 2017
First published:	2017
Editors:	Le Lu • Yefeng Zheng • Gustavo Carneiro • Lin Yang
Dimensions:	235 x 155 x 23mm (L x W x T)
Format:	Hardcover
Pages:	326
Edition:	1st ed. 2017
ISBN-13:	978-3-319-42998-4
Categories:	Books > Medicine > Other branches of medicine > Medical imaging > General Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision Books > Computing & IT > Applications of computing > Artificial intelligence > Neural networks Books > Computing & IT > Applications of computing > Image processing > General
LSN:	3-319-42998-1
Barcode:	9783319429984

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