CAT: Constrained Adversarial Training for Anatomically-Plausible Semi-Supervised Segmentation
Author:
Affiliation:
1. Software and IT Department, École de Technologie Supérieure (ETS), Montreal, Canada
2. Department of System Engineering, École de Technologie Supérieure (ETS), Montreal, Canada
3. School of Software, Shandong University, Jinan, China
Funder
Natural Sciences and Engineering Research Council of Canada
National Natural Science Foundation of China Joint Fund with Zhejiang Integration of Informatization and Industrialization under Key Project
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software
Link
http://xplorestaging.ieee.org/ielx7/42/10198906/10038734.pdf?arnumber=10038734
Reference42 articles.
1. Constrained-CNN losses for weakly supervised segmentation
2. Finding the convex hull of a simple polygon
3. Deep Atlas Network for Efficient 3D Left Ventricle Segmentation on Echocardiography
4. Simple statistical gradient-following algorithms for connectionist reinforcement learning
5. Constrained Deep Weak Supervision for Histopathology Image Segmentation
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