Raghav Mehta

KR Mangalam University — India

Medicine · Health Sciences

10h-index622citations68works0.42yr avg
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Research Topics

Radiomics and Machine Learning in Medical Imaging(19), Advanced Neural Network Applications(13), Brain Tumor Detection and Classification(13), AI in cancer detection(11), Medical Image Segmentation Techniques(9)

Publications68 total

Adapting Segment Anything Model for Multi Organ Medical Image Segmentation
2025
Segmentor-Guided Counterfactual Fine-Tuning for Locally Coherent and Targeted Image Synthesis
arXiv (Cornell University)·2025Open Access
Delineation Uncertainty from Clinician Ranges in Cervical Cancer Radiotherapy Planning
Lecture notes in computer science·2025
Segmentor-Guided Counterfactual Fine-Tuning for Locally Coherent and Targeted Image Synthesis
Lecture notes in computer science·2025
UNSURF: Uncertainty Quantification for Cortical Surface Reconstruction of Clinical Brain MRIs
Lecture notes in computer science·2025
CF-Seg: Counterfactuals Meet Segmentation
Lecture notes in computer science·2025· 1 cited
Automatic Dataset Shift Identification to Support Safe Deployment of Medical Imaging AI
Lecture notes in computer science·2025· 3 cited
Exploring the Interplay of Label Bias with Subgroup Size and Separability: A Case Study in Mammographic Density Classification
Lecture notes in computer science·2025
Flow Stochastic Segmentation Networks
arXiv (Cornell University)·2025Open Access
Exploring the interplay of label bias with subgroup size and separability: A case study in mammographic density classification
arXiv (Cornell University)·2025Open Access
Where are we with calibration under dataset shift in image classification?
arXiv (Cornell University)·2025Open Access
Cardiovascular disease classification using radiomics and geometric features from cardiac CT
arXiv (Cornell University)·2025Open Access
CF-Seg: Counterfactuals meet Segmentation
arXiv (Cornell University)·2025Open Access
UNSURF: Uncertainty Quantification for Cortical Surface Reconstruction of Clinical Brain MRIs
arXiv (Cornell University)·2025Open Access
Automatic dataset shift identification to support safe deployment of medical imaging AI
arXiv (Cornell University)·2024· 1 citedOpen Access
Genetics and Malignant Hyperthermia
ASA Monitor·2024· 1 cited
Exploring Compound Loss Functions for Brain Tumor Segmentation
Lecture notes in computer science·2024
Current AI applications in neurology: Brain imaging
Journal of the Neurological Sciences·2023
Confusing Large Models by Confusing Small Models
2023
Debiasing Counterfactuals In the Presence of Spurious Correlations
arXiv (Cornell University)·2023Open Access
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Frequent Co-authors

Tal Arbel(21), Douglas L. Arnold(9), Brennan Nichyporuk(7), Ben Glocker(7), Jayanthi Sivaswamy(6), Jean-Pierre Falet(5), Angelos Filos(4), Yarin Gal(4), Sotirios A. Tsaftaris(4), Justin Szeto(4), Mélanie Roschewitz(4), Fabio De Sousa Ribeiro(4), Ujjwal Baid(3), Chiharu Sako(3), Richard McKinley(3), Michael Rebsamen(3), Piotr Radojewski(3), Gowtham Krishnan Murugesan(3), Chandrasekharan Kesavadas(3), Honey Jindal(3)