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eess.IV2021
ASC-Net: Unsupervised Medical Anomaly Segmentation Using an Adversarial-based Selective Cutting Network
Raunak Dey, Wenbo Sun, Haibo Xu +1
In this paper we consider the problem of unsupervised anomaly segmentation in medical images, which has attracted increasing attention in recent years due to the expensive pixel-le…
cs.CV2021★ 15 cited
ASC-Net : Adversarial-based Selective Network for Unsupervised Anomaly Segmentation
Raunak Dey, Yi Hong
We introduce a neural network framework, utilizing adversarial learning to partition an image into two cuts, with one cut falling into a reference distribution provided by the user…