13 citations · 32 across the 12 of their papers we have counts for
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cs.CV2023
Interpretability-Aware Vision Transformer
Yao Qiang, Chengyin Li, Prashant Khanduri +1
Vision Transformers (ViTs) have become prominent models for solving various vision tasks. However, the interpretability of ViTs has not kept pace with their promising performance.…
cs.CV2023
AutoProSAM: Automated Prompting SAM for 3D Multi-Organ Segmentation
Chengyin Li, Prashant Khanduri, Yao Qiang +3
Segment Anything Model (SAM) is one of the pioneering prompt-based foundation models for image segmentation and has been rapidly adopted for various medical imaging applications. H…
cs.CV2019
Vispi: Automatic Visual Perception and Interpretation of Chest X-rays
Xin Li, Rui Cao, Dongxiao Zhu
Medical imaging contains the essential information for rendering diagnostic and treatment decisions. Inspecting (visual perception) and interpreting image to generate a report are…