6 papers · 1 filter
SeVeR: Selective Visual Exposure and Retrieval for 3D Medical Image Question Answering
Yaojun Hu, Danyang Tu, Yang Liu +8
Volumetric medical VQA requires reasoning over long and redundant 3D visual token sequences, especially in multi-sequence MRI where complementary modalities provide diverse diagnos…
D3O: Dynamic Distribution Distillation for Ordinal Regression
Chunlai Dong, Yaojun Hu, Yuyang Xu +2
Ordinal regression is widely used in scenarios where labels are discrete yet inherently ordered. In practice, however, ordinal labels are often obtained by discretizing underlying…
HDMoE: A Hierarchical Decoupling-Fusion Mixture-of-Experts Framework for Multimodal Cancer Survival Prediction
Huayi Wang, Haochao Ying, Yuyang Xu +5
Multimodal survival prediction, a crucial yet challenging task, demands the integration of multimodal medical data (\eg Whole Slide Images (WSIs) and Genomic Profiles) to achieve a…
Decouple, Reorganize, and Fuse: A Multimodal Framework for Cancer Survival Prediction
Huayi Wang, Haochao Ying, Yuyang Xu +5
Cancer survival analysis commonly integrates information across diverse medical modalities to make survival-time predictions. Existing methods primarily focus on extracting differe…
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset
Jinhong Wang, Shuo Tong, Jian liu +6
Visual rating is an essential capability of artificial intelligence (AI) for multi-dimensional quantification of visual content, primarily applied in ordinal regression (OR) tasks…
Dual-level Fuzzy Learning with Patch Guidance for Image Ordinal Regression
Chunlai Dong, Haochao Ying, Qibo Qiu +3
Ordinal regression bridges regression and classification by assigning objects to ordered classes. While human experts rely on discriminative patch-level features for decisions, cur…