4 papers
Convex Potential Learning for Optimal Transport Between Medical Images
Hongyu Kan, Ivan Medri, Natasha Ironside +4
Computing optimal transport maps between medical images plays a fundamental role in morphological analysis. However, existing methods are either difficult to scale to large 3D medi…
3D Transport-based Morphometry (3D-TBM) for medical image analysis
Hongyu Kan, Kristofor Pas, Ivan Medri +5
Transport-Based Morphometry (TBM) has emerged as a new framework for 3D medical image analysis. By embedding images into a transport domain via invertible transformations, TBM faci…
FlashOmni: A Unified Sparse Attention Engine for Diffusion Transformers
Liang Qiao, Yue Dai, Yeqi Huang +3
Multi-Modal Diffusion Transformers (DiTs) demonstrate exceptional capabilities in visual synthesis, yet their deployment remains constrained by substantial computational demands. T…
H-DenseFormer: An Efficient Hybrid Densely Connected Transformer for Multimodal Tumor Segmentation
Jun Shi, Hongyu Kan, Shulan Ruan +6
Recently, deep learning methods have been widely used for tumor segmentation of multimodal medical images with promising results. However, most existing methods are limited by insu…