9 papers
Spatial Masked-Set Learning for Sparse Multi-Shell Diffusion MRI Signal Synthesis
Yousef Sadegheih, Pratibha Kumari, Dorit Merhof
Dense multi-shell diffusion MRI provides rich q-space information but requires long acquisition times. We propose a spatial masked-set framework for sparse multi-shell diffusion MR…
Footprint-Guided Exemplar-Free Continual Histopathology Report Generation
Pratibha Kumari, Daniel Reisenbüchler, Afshin Bozorgpour +3
Rapid progress in vision-language modeling has enabled pathology report generation from gigapixel whole-slide images, but most approaches assume static training with simultaneous a…
Towards Modality-Agnostic Continual Domain-Incremental Brain Lesion Segmentation
Yousef Sadegheih, Dorit Merhof, Pratibha Kumari
Brain lesion segmentation from multi-modal MRI often assumes fixed modality sets or predefined pathologies, making existing models difficult to adapt across cohorts and imaging pro…
Modality-Agnostic Brain Lesion Segmentation with Privacy-aware Continual Learning
Yousef Sadegheih, Pratibha Kumari, Dorit Merhof
Traditional brain lesion segmentation models for multi-modal MRI are typically tailored to specific pathologies, relying on datasets with predefined modalities. Adapting to new MRI…
LHU-Net: a Lean Hybrid U-Net for Cost-efficient, High-performance Volumetric Segmentation
Yousef Sadegheih, Afshin Bozorgpour, Pratibha Kumari +2
The rise of Transformer architectures has advanced medical image segmentation, leading to hybrid models that combine Convolutional Neural Networks (CNNs) and Transformers. However,…
Attention-based Generative Latent Replay: A Continual Learning Approach for WSI Analysis
Pratibha Kumari, Daniel Reisenbüchler, Afshin Bozorgpour +3
Whole slide image (WSI) classification has emerged as a powerful tool in computational pathology, but remains constrained by domain shifts, e.g., due to different organs, diseases,…