STAMP: Simultaneous Training and Model Pruning for low data regimes in medical image segmentation-Reference-Cited by-同舟云学术

STAMP: Simultaneous Training and Model Pruning for low data regimes in medical image segmentation

Published:2022-10 Issue: Volume:81 Page:102583
ISSN:1361-8415
Container-title:Medical Image Analysis
language:en
Short-container-title:Medical Image Analysis

Author:

Dinsdale Nicola K.,Jenkinson Mark^ORCID,Namburete Ana I.L.

Funder

Wellcome Trust

NIHR Imperial Biomedical Research Centre

UKRI

NIHR Oxford Biomedical Research Centre

Medical Research Council

Engineering and Physical Sciences Research Council

National Institute for Health and Care Research

Royal Academy of Engineering

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference44 articles.

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3. 3D U-Net: Learning dense volumetric segmentation from sparse annotation;Cicek,2016

4. RandomOut: Using a convolutional gradient norm to win the filter lottery;Cohen,2016

5. Optimal brain damage;Cun,1990

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