Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures

Hayit Greenspan

ISBN 10: 3030326888 / ISBN 13: 9783030326883

Published by Springer International Publishing, Springer Nature Switzerland Okt 2019, 2019

About this Item

Neuware -This book constitutes the refereed proceedings of the First International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2019, and the 8th International Workshop on Clinical Image-Based Procedures, CLIP 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019.For UNSURE 2019, 8 papers from 15 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world.CLIP 2019 accepted 11 papers from the 15 submissions received. The workshops provides a forum for work centred on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 212 pp. Englisch.

Seller Inventory # 9783030326883

Bibliographic Details

• Title: Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures
• Publisher: Springer International Publishing, Springer Nature Switzerland Okt 2019
• Publication Date: 2019
• Language: English
• ISBN 10: 3030326888
• ISBN 13: 9783030326883
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

This book constitutes the refereed proceedings of the First International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2019, and the 8^th International Workshop on Clinical Image-Based Procedures, CLIP 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019.

For UNSURE 2019, 8 papers from 15 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world.

CLIP 2019 accepted 11 papers from the 15 submissions received. The workshops provides a forum for work centred on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.