1 citations · 1 across the 4 of their papers we have counts for
5 papers
Open ultrasound foundation model for robust segmentation and clinical measurement across heterogeneous settings
Chao Qin, Fahad Shahbaz Khan, Salman Khan +4
Ultrasound is the most widely deployed imaging modality worldwide, yet clinical AI remains fragmented into narrow single-task models that fail when device, operator, or anatomy cha…
Revisiting Global Token Mixing in Task-Dependent MRI Restoration: Insights from Minimal Gated CNN Baselines
Xiangjian Hou, Chao Qin, Chang Ni +3
Global token mixing, implemented via self-attention or state-space sequence models, has become a popular model design choice for MRI restoration. However, MRI restoration tasks dif…
All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages
Ashmal Vayani, Dinura Dissanayake, Hasindri Watawana +66
Existing Large Multimodal Models (LMMs) generally focus on only a few regions and languages. As LMMs continue to improve, it is increasingly important to ensure they understand cul…
DB-SAM: Delving into High Quality Universal Medical Image Segmentation
Chao Qin, Jiale Cao, Huazhu Fu +2
Recently, the Segment Anything Model (SAM) has demonstrated promising segmentation capabilities in a variety of downstream segmentation tasks. However in the context of universal m…
A Spatial-Temporal Deformable Attention based Framework for Breast Lesion Detection in Videos
Chao Qin, Jiale Cao, Huazhu Fu +2
Detecting breast lesion in videos is crucial for computer-aided diagnosis. Existing video-based breast lesion detection approaches typically perform temporal feature aggregation of…