7 papers
Equi-ViT: Rotational Equivariant Vision Transformer for Robust Histopathology Analysis
Fuyao Chen, Yuexi Du, Elèonore V. Lieffrig +2
Vision Transformers (ViTs) have gained rapid adoption in computational pathology for their ability to model long-range dependencies through self-attention, addressing the limitatio…
Spatially-Aware Evaluation of Segmentation Uncertainty
Tal Zeevi, Eléonore V. Lieffrig, Lawrence H. Staib +1
Uncertainty maps highlight unreliable regions in segmentation predictions. However, most uncertainty evaluation metrics treat voxels independently, ignoring spatial context and ana…
Equivariant Imaging Biomarkers for Robust Unsupervised Segmentation of Histopathology
Fuyao Chen, Yuexi Du, Tal Zeevi +2
Histopathology evaluation of tissue specimens through microscopic examination is essential for accurate disease diagnosis and prognosis. However, traditional manual analysis by spe…
GMR-Conv: An Efficient Rotation and Reflection Equivariant Convolution Kernel Using Gaussian Mixture Rings
Yuexi Du, Jiazhen Zhang, Nicha C. Dvornek +1
Symmetry, where certain features remain invariant under geometric transformations, can often serve as a powerful prior in designing convolutional neural networks (CNNs). While conv…
Improved Vessel Segmentation with Symmetric Rotation-Equivariant U-Net
Jiazhen Zhang, Yuexi Du, Nicha C. Dvornek +1
Automated segmentation plays a pivotal role in medical image analysis and computer-assisted interventions. Despite the promising performance of existing methods based on convolutio…
Enhancing Uncertainty Estimation in Semantic Segmentation via Monte-Carlo Frequency Dropout
Tal Zeevi, Lawrence H. Staib, John A. Onofrey
Monte-Carlo (MC) Dropout provides a practical solution for estimating predictive distributions in deterministic neural networks. Traditional dropout, applied within the signal spac…