12 papers
MVC-Bench: Benchmarking Calibration of Medical Vision-Language Models
Ashshak Sharifdeen, Shihab Aaqil Ahamed, Ufaq Khan +6
Reliable evaluation of vision-language models (VLMs) and medical vision-language models (Medical-VLMs) requires calibrated confidence, particularly under realistic clinical conditi…
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…
Graph-of-Differences: Anatomy-Structured Difference Alignment for Medical Image Re-Identification
Nichula Wasalathilaka, Abhijit Das, Imran Razzak +1
Medical image re-identification (MedReID) enables longitudinal patient linkage but remains vulnerable to shortcut learning and often produces decisions that clinicians cannot audit…
PROTON: Prototype-Based Test-Time Online OOD Detection for Medical VLMs
Abhijit Das, Nichula Wasalathilaka, Yifan Lu +4
Medical vision-language models (VLMs) enable zero-shot clinical image classification, yet reliably detecting out-of-distribution (OOD) inputs at deployment remains an open problem.…
MS-DKC: A Dataset Knowledge Card Framework for Designing and Adapting Medical Image Segmentation Models
Tariq M. Khan, Syed Saud Naqvi, Thantrira Porntaveetus +4
Medical image segmentation is often framed as a search for stronger architectures, but this can obscure a more fundamental question: what does the dataset require from the model? I…
VGS-Decoding: Visual Grounding Score Guided Decoding for Hallucination Mitigation in Medical VLMs
Govinda Kolli, Adinath Madhavrao Dukre, Behzad Bozorgtabar +2
Medical Vision-Language Models (VLMs) often hallucinate by generating responses based on language priors rather than visual evidence, posing risks in clinical applications. We prop…
TuLaBM: Tumor-Biased Latent Bridge Matching for Contrast-Enhanced MRI Synthesis
Atharva Rege, Adinath Madhavrao Dukre, Numan Balci +2
Contrast-enhanced magnetic resonance imaging (CE-MRI) plays a crucial role in brain tumor assessment; however, its acquisition requires gadolinium-based contrast agents (GBCAs), wh…