1 citations · 2 across the 8 of their papers we have counts for
3 papers · 1 filter
IterMask2: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI
Ziyun Liang, Xiaoqing Guo, J. Alison Noble +1
Unsupervised anomaly segmentation approaches to pathology segmentation train a model on images of healthy subjects, that they define as the 'normal' data distribution. At inference…
Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities
Felix Wagner, Wentian Xu, Pramit Saha +7
Segmentation models for brain lesions in MRI are typically developed for a specific disease and trained on data with a predefined set of MRI modalities. Such models cannot segment…
Modality Cycles with Masked Conditional Diffusion for Unsupervised Anomaly Segmentation in MRI
Ziyun Liang, Harry Anthony, Felix Wagner +1
Unsupervised anomaly segmentation aims to detect patterns that are distinct from any patterns processed during training, commonly called abnormal or out-of-distribution patterns, w…