A hybrid approach to tissue-based intensity standardization of brain MRI images. - Raghav Mehta; Jayanthi Sivaswamy (ISBI, 2016)

M-net: A Convolutional Neural Network for deep brain structure segmentation. - Raghav Mehta; Jayanthi Sivaswamy (ISBI, 2017)

High performance training of deep neural networks using pipelined hardware acceleration and distributed memory. - Raghav Mehta; Yuyang Huang; Mingxi Cheng; Shrey Bagga; Nishant Mathur; Ji Li 006; Jeffrey Draper; Shahin Nazarian (ISQED, 2018)

To Learn or Not to Learn Features for Deformable Registration? - Aabhas Majumdar; Raghav Mehta; Jayanthi Sivaswamy (MLCN/DLF/iMIMIC@MICCAI, 2018)

RS-Net: Regression-Segmentation 3D CNN for Synthesis of Full Resolution Missing Brain MRI in the Presence of Tumours. - Raghav Mehta; Tal Arbel (SASHIMI@MICCAI, 2018)

3D U-Net for Brain Tumour Segmentation. - Raghav Mehta; Tal Arbel (BrainLes@MICCAI (2), 2018)

NormCo: Deep Disease Normalization for Biomedical Knowledge Base Construction. - Dustin Wright 002; Yannis Katsis; Raghav Mehta; Chun-Nan Hsu (AKBC, 2019)

Improving Pathological Structure Segmentation via Transfer Learning Across Diseases. - Barleen Kaur; Paul Lemaître; Raghav Mehta; Nazanin Mohammadi Sepahvand; Doina Precup; Douglas L. Arnold; Tal Arbel (DART/MIL3ID@MICCAI, 2019)

Propagating Uncertainty Across Cascaded Medical Imaging Tasks for Improved Deep Learning Inference. - Raghav Mehta; Thomas Christinck; Tanya Nair; Paul Lemaître; Douglas L. Arnold; Tal Arbel (UNSURE/CLIP@MICCAI, 2019)

Hybrid Cell Assignment and Sizing for Power, Area, Delay-Product Optimization of SRAM Arrays. - Ghasem Pasandi; Raghav Mehta; Massoud Pedram; Shahin Nazarian (IEEE Trans. Circuits Syst. II Express Briefs, 2019)

Uncertainty Evaluation Metric for Brain Tumour Segmentation. - Raghav Mehta; Angelos Filos; Yarin Gal; Tal Arbel (CoRR, 2020)

Cohort Bias Adaptation in Aggregated Datasets for Lesion Segmentation. - Brennan Nichyporuk; Jillian Cardinell; Justin Szeto; Raghav Mehta; Sotirios A. Tsaftaris; Douglas L. Arnold; Tal Arbel (DART/FAIR@MICCAI, 2021)

HAD-Net: A Hierarchical Adversarial Knowledge Distillation Network for Improved Enhanced Tumour Segmentation Without Post-Contrast Images. - Saverio Vadacchino; Raghav Mehta; Nazanin Mohammadi Sepahvand; Brennan Nichyporuk; James J. Clark; Tal Arbel (MIDL, 2021)

Sub-cortical structure segmentation database for young population. - Jayanthi Sivaswamy; Alphin J. Thottupattu; Mythri V; Raghav Mehta; R. Sheelakumari; Chandrasekharan Kesavadas (CoRR, 2021)

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results. - Raghav Mehta; Angelos Filos; Ujjwal Baid; Chiharu Sako; Richard McKinley; Michael Rebsamen; Katrin Dätwyler; Raphael Meier; Piotr Radojewski; Gowtham Krishnan Murugesan; Sahil S. Nalawade; Chandan Ganesh; et al. (CoRR, 2021)

Information Gain Sampling for Active Learning in Medical Image Classification. - Raghav Mehta; Changjian Shui; Brennan Nichyporuk; Tal Arbel (UNSURE@MICCAI, 2022)

Rethinking Generalization: The Impact of Annotation Style on Medical Image Segmentation. - Brennan Nichyporuk; Jillian Cardinell; Justin Szeto; Raghav Mehta; Jean-Pierre R. Falet; Douglas L. Arnold; Sotirios A. Tsaftaris; Tal Arbel (CoRR, 2022)

You Only Need a Good Embeddings Extractor to Fix Spurious Correlations. - Raghav Mehta; Vítor Albiero; Li Chen; Ivan Evtimov; Tamar Glaser; Zhiheng Li 002; Tal Hassner (CoRR, 2022)

Propagating Uncertainty Across Cascaded Medical Imaging Tasks for Improved Deep Learning Inference. - Raghav Mehta; Thomas Christinck; Tanya Nair; Aurélie Bussy; Swapna Premasiri; Manuela Costantino; M. Mallar Chakravarthy; Douglas L. Arnold; Yarin Gal; Tal Arbel (IEEE Trans. Medical Imaging, 2022)

Debiasing Counterfactuals in the Presence of Spurious Correlations. - Amar Kumar; Nima Fathi; Raghav Mehta; Brennan Nichyporuk; Jean-Pierre R. Falet; Sotirios A. Tsaftaris; Tal Arbel (CLIP/FAIMI/EPIMI@MICCAI, 2023)

Confusing Large Models by Confusing Small Models. - Vítor Albiero; Raghav Mehta; Ivan Evtimov; Samuel J. Bell; Levent Sagun; Aram Markosyan (ICCV (Workshops), 2023)

Improving Image-Based Precision Medicine with Uncertainty-Aware Causal Models. - Joshua Durso-Finley; Jean-Pierre R. Falet; Raghav Mehta; Douglas L. Arnold; Nick Pawlowski; Tal Arbel (MICCAI (5), 2023)

Exploring Compound Loss Functions for Brain Tumor Segmentation. - Anita Kriz; Raghav Mehta; Brennan Nichyporuk; Tal Arbel (BraTS/CrossMoDA@MICCAI, 2023)

Mitigating Calibration Bias Without Fixed Attribute Grouping for Improved Fairness in Medical Imaging Analysis. - Changjian Shui; Justin Szeto; Raghav Mehta; Douglas L. Arnold; Tal Arbel (MICCAI (3), 2023)

Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis. - Raghav Mehta; Changjian Shui; Tal Arbel (MIDL, 2023)

Automatic dataset shift identification to support root cause analysis of AI performance drift. - Mélanie Roschewitz; Raghav Mehta; Charles Jones; Ben Glocker (CoRR, 2024)

UNSURF: Uncertainty Quantification for Cortical Surface Reconstruction of Clinical Brain MRIs. - Raghav Mehta; Karthik Gopinath; Ben Glocker; Juan Eugenio Iglesias (CoRR, 2025)

Decoupled Classifier-Free Guidance for Counterfactual Diffusion Models. - Tian Xia; Fabio De Sousa Ribeiro; Rajat Rasal; Avinash Kori; Raghav Mehta; Ben Glocker (CoRR, 2025)

CF-Seg: Counterfactuals meet Segmentation. - Raghav Mehta; Fabio De Sousa Ribeiro; Tian Xia; Mélanie Roschewitz; Ainkaran Santhirasekaram; Dominic C. Marshall; Ben Glocker (CoRR, 2025)

Cardiovascular disease classification using radiomics and geometric features from cardiac CT. - Ajay Mittal; Raghav Mehta; Omar Todd; Philipp Seeböck; Georg Langs; Ben Glocker (CoRR, 2025)

Where are we with calibration under dataset shift in image classification? - Mélanie Roschewitz; Raghav Mehta; Fabio De Sousa Ribeiro; Ben Glocker (CoRR, 2025)

Exploring the interplay of label bias with subgroup size and separability: A case study in mammographic density classification. - Emma A. M. Stanley; Raghav Mehta; Mélanie Roschewitz; Nils D. Forkert; Ben Glocker (CoRR, 2025)

Flow Stochastic Segmentation Networks. - Fabio De Sousa Ribeiro; Omar Todd; Charles Jones; Avinash Kori; Raghav Mehta; Ben Glocker (CoRR, 2025)