11 papers
Counterfactual Anatomy-guided Spatial-Temporal Decoding for Annotation-Free Hallucination Mitigation in Medical VLMs
Yifan Lu, Adinath Dukre, Abhijit Das +4
Medical vision-language models (Med-VLMs) have demonstrated strong performance on medical visual question answering, yet they remain prone to hallucination, generating clinically u…
Causal-RetiGraph: Cross-Cohort Retinal Support and Same-Subject Pathway Analysis for Diabetic Retinopathy
Inam Ullah, Imran Razzak, Shoaib Jameel
Diabetic retinopathy (DR) is a local retinal lesion process and a visible manifestation of systemic microvascular injury. Modern retinal AI can grade images accurately, but often l…
TAVR-VLM: Risk-Conditioned Causal Grounding for Hallucination-Resistant Report Generation
Zhixiang Lu, Xiwei Liu, Sifan Song +5
Transcatheter Aortic Valve Replacement (TAVR) planning requires meticulous multimodal reasoning. However, adapting Multimodal Large Language Models (MLLMs) to this high-stakes doma…
RetiSEM: Generalising Causal Models for Fragmented Biomedical Data
Inam Ullah, Imran Razzak, Shoaib Jameel
Learning causal models from fragmented biomedical data is challenging because clinical, molecular, and imaging variables are often incomplete or not jointly observed. We propose Re…
A Dual Edge Spatial Jacobian Image Graph for Interpretable Diabetic Retinopathy Grading
Inam Ullah, Imran Razzak, Shoaib Jameel
Automated diabetic retinopathy (DR) grading from colour fundus photographs can achieve strong predictive performance, but clinical interpretation requires more than an image-level…
EnTrust: Modeling Inter-Modal Conflict for Trustworthy Multimodal Medical Image Analysis
Dwarikanath Mahapatra, Abhijit Das, Behzad Bozorgtabar +5
Multimodal medical imaging fuses complementary anatomical and functional information, yet modalities frequently disagree in pathologically heterogeneous regions. Current segmentati…