Deep Q-Network-Driven Catheter Segmentation in 3D US by Hybrid Constrained Semi-Supervised Learning and Dual-UNet

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Original languageEnglish
Title of host publicationProceedings of the 23rd International Conference on Medical Image Computing & Computer Assisted Intervention
Publication statusAccepted/In press - 2020
Event23rd International Conference on Medical Image Computing & Computer Assisted Intervention - Lima, Peru
Duration: 4 Oct 20208 Oct 2020
https://www.miccai2020.org/en/CALLS.html

Conference

Conference23rd International Conference on Medical Image Computing & Computer Assisted Intervention
CountryPeru
CityLima
Period4/10/208/10/20
Internet address

Cite this

Yang, H., Shan, C., Kolen, A. F., & de With, P. H. N. (Accepted/In press). Deep Q-Network-Driven Catheter Segmentation in 3D US by Hybrid Constrained Semi-Supervised Learning and Dual-UNet. In Proceedings of the 23rd International Conference on Medical Image Computing & Computer Assisted Intervention