13 papers
Evi-Steer: Learning to Steer Biomedical Vision-Language Models through Efficient and Generalizable Evidential Tuning
Taha Koleilat, Hassan Rivaz, Yiming Xiao
Parameter-efficient adaptation of vision-language foundation models is crucial for precise multimodal understanding of biomedical images, yet existing methods remain deterministic…
VesselSim: learning 3D blood vessel segmentation without expert annotations
Erin Rainville, Melissa Ananian, Tristan Mirolla +2
Blood vessel segmentation is a core task in medical image analysis for the care of vascular diseases and surgical planning, yet the challenges of providing expert vascular annotati…
CLIP-SVD: Efficient and Interpretable Vision-Language Adaptation via Singular Values
Taha Koleilat, Hassan Rivaz, Yiming Xiao
Vision-language models (VLMs) like CLIP have shown impressive zero-shot and few-shot learning capabilities across diverse applications. However, adapting these models to new fine-g…
Sparse Spectral LoRA: Routed Experts for Medical VLMs
Omid Nejati Manzari, Hojat Asgariandehkordi, Taha Koleilat +2
Large vision-language models (VLMs) excel on general benchmarks but often lack robustness in medical imaging, where heterogeneous supervision induces cross-dataset interference and…
Medical Image Classification with KAN-Integrated Transformers and Dilated Neighborhood Attention
Omid Nejati Manzari, Hojat Asgariandehkordi, Taha Koleilat +2
Convolutional networks, transformers, hybrid models, and Mamba-based architectures have demonstrated strong performance across various medical image classification tasks. However,…
DINOMotion: advanced robust tissue motion tracking with DINOv2 in 2D-Cine MRI-guided radiotherapy
Soorena Salari, Catherine Spino, Laurie-Anne Pharand +4
Accurate tissue motion tracking is critical to ensure treatment outcome and safety in 2D-Cine MRI-guided radiotherapy. This is typically achieved by registration of sequential imag…