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Machine learning in medical imaging1...

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Machine learning in medical imaging10th International Workshop, MLMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning in medical imagingedited by Heung-Il Suk ... [et al.].
Reminder of title:	10th International Workshop, MLMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019 : proceedings /
remainder title:	MLMI 2019
other author:	Suk, Heung-Il.
corporate name:
Published:	Cham :Springer International Publishing :2019.
Description:	xviii, 695 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Machine learningCongresses.
Online resource:	https://doi.org/10.1007/978-3-030-32692-0
ISBN:	9783030326920$q(electronic bk.)

Machine learning in medical imaging10th International Workshop, MLMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019 : proceedings /
Machine learning in medical imaging10th International Workshop, MLMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019 : proceedings /[electronic resource] :MLMI 2019edited by Heung-Il Suk ... [et al.]. - Cham :Springer International Publishing :2019. - xviii, 695 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,118610302-9743 ;. - Lecture notes in computer science ;4891..

This book constitutes the proceedings of the 10th International Workshop on Machine Learning in Medical Imaging, MLMI 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. The 78 papers presented in this volume were carefully reviewed and selected from 158 submissions. They focus on major trends and challenges in the area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.

ISBN: 9783030326920$q(electronic bk.)

Standard No.: 10.1007/978-3-030-32692-0doiSubjects--Topical Terms:

384498
Machine learning
--Congresses.

LC Class. No.: RC78.7.D53 / M55 2019

Dewey Class. No.: 006.6

Machine learning in medical imaging10th International Workshop, MLMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019 : proceedings /
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