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Found 4 papers, 3 papers with code
Asymmetry Disentanglement Network for Interpretable Acute Ischemic Stroke Infarct Segmentation in Non-Contrast CT Scans
In this paper, we propose a novel Asymmetry Disentanglement Network (ADN) to automatically separate pathological asymmetries and intrinsic anatomical asymmetries in NCCTs for more effective and interpretable AIS segmentation.
Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image Segmentation
We also propose a new mixture-of-experts (MoE) based decoder, which treats the feature maps from the encoder as experts and selects a suitable set of expert features to predict the label for each pixel.
DeepStroke: An Efficient Stroke Screening Framework for Emergency Rooms with Multimodal Adversarial Deep Learning
In an emergency room (ER) setting, stroke triage or screening is a common challenge.
LambdaUNet: 2.5D Stroke Lesion Segmentation of Diffusion-weighted MR Images
Thus, it is not ideal to apply most existing segmentation methods as they are designed for either 2D or 3D images.
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