Raunak Dey, Yi Hong. ASC-Net: Adversarial-Based Selective Network for Unsupervised Anomaly Segmentation. In Marleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert, editors, Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27 - October 1, 2021, Proceedings, Part V. Volume 12905 of Lecture Notes in Computer Science, pages 236-247, Springer, 2021. [doi]
@inproceedings{DeyH21-0,
title = {ASC-Net: Adversarial-Based Selective Network for Unsupervised Anomaly Segmentation},
author = {Raunak Dey and Yi Hong},
year = {2021},
doi = {10.1007/978-3-030-87240-3_23},
url = {https://doi.org/10.1007/978-3-030-87240-3_23},
researchr = {https://researchr.org/publication/DeyH21-0},
cites = {0},
citedby = {0},
pages = {236-247},
booktitle = {Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27 - October 1, 2021, Proceedings, Part V},
editor = {Marleen de Bruijne and Philippe C. Cattin and Stéphane Cotin and Nicolas Padoy and Stefanie Speidel and Yefeng Zheng and Caroline Essert},
volume = {12905},
series = {Lecture Notes in Computer Science},
publisher = {Springer},
isbn = {978-3-030-87240-3},
}