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eess.IV2024
SPA: Efficient User-Preference Alignment against Uncertainty in Medical Image Segmentation
Jiayuan Zhu, Junde Wu, Cheng Ouyang +2
Medical image segmentation data inherently contain uncertainty. This can stem from both imperfect image quality and variability in labeling preferences on ambiguous pixels, which d…
eess.IV2024
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…
eess.IV2024★ 1 cited
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…