168 citations · 293 across the 13 of their papers we have counts for
4 papers · 1 filter
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…
DDR-Net: Dividing and Downsampling Mixed Network for Diffeomorphic Image Registration
Ankita Joshi, Yi Hong
Deep diffeomorphic registration faces significant challenges for high-dimensional images, especially in terms of memory limits. Existing approaches either downsample original image…
MDA-Net: Multi-Dimensional Attention-Based Neural Network for 3D Image Segmentation
Rutu Gandhi, Yi Hong
Segmenting an entire 3D image often has high computational complexity and requires large memory consumption; by contrast, performing volumetric segmentation in a slice-by-slice man…
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…