Weakly-Supervised teacher-Student network for liver tumor segmentation from non-enhanced images-Reference-Cited by-同舟云学术

Weakly-Supervised teacher-Student network for liver tumor segmentation from non-enhanced images

Published:2021-05 Issue: Volume:70 Page:102005
ISSN:1361-8415
Container-title:Medical Image Analysis
language:en
Short-container-title:Medical Image Analysis

Author:

Zhang Dong,Chen Bo,Chong Jaron,Li Shuo^ORCID

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

Reference52 articles.

1. Automatic view planning with multi-scale deep reinforcement learning agents;Alansary,2018

2. Hepatux-a semiautomatic liver segmentation system;Beck;3D Segmentation in The Clinic: A Grand Challenge,2007

3. Liver segmentation in ct data: a segmentation refinement approach;Beichel12;Proceedings of” 3D Segmentation in The Clinic: A Grand Challenge,2007

4. The liver tumor segmentation benchmark (lits);Bilic;arXiv preprint arXiv:1901.04056,2019

5. A hybrid user interface for manipulation of volumetric medical data;Bornik,2006

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