Raghav Mehta
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
18
Venues
2
Active years
2018–2025
Best venue rank
A*
Where they publish
Papers
18 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICCV | Flow Stochastic Segmentation Networks. | Fabio De Sousa Ribeiro, Omar Todd, Charles Jones, Avinash Kori, Raghav Mehta, Ben Glocker |
| 2025 | MICCAI | UNSURF: Uncertainty Quantification for Cortical Surface Reconstruction of Clinical Brain MRIs. | Karthik Gopinath, Raghav Mehta, Ben Glocker, Juan Eugenio Iglesias |
| 2025 | MICCAI | CF-Seg: Counterfactuals Meet Segmentation. | Raghav Mehta, Fabio De Sousa Ribeiro, Tian Xia, Mlanie Roschewitz, Ainkaran Santhirasekaram, Dominic C. Marshall, Ben Glocker |
| 2025 | MICCAI | Cardiovascular Disease Classification Using Radiomics and Geometric Features from Cardiac CT. | Ajay Mittal, Raghav Mehta, Omar Todd, Philipp Seebck, Georg Langs, Ben Glocker |
| 2025 | MICCAI | Automatic Dataset Shift Identification to Support Safe Deployment of Medical Imaging AI. | Mlanie Roschewitz, Raghav Mehta, Charles Jones, Ben Glocker |
| 2025 | MICCAI | Exploring the Interplay of Label Bias with Subgroup Size and Separability: A Case Study in Mammographic Density Classification. | Emma A. M. Stanley, Raghav Mehta, Mlanie Roschewitz, Nils D. Forkert, Ben Glocker |
| 2025 | MICCAI | Delineation Uncertainty from Clinician Ranges in Cervical Cancer Radiotherapy Planning. | Omar Todd, Sooha Kim, Katherine Mackay, Raghav Mehta, Fabio De Sousa Ribeiro, David Bernstein, Alexandra Taylor, Ben Glocker |
| 2025 | MICCAI | Segmentor-Guided Counterfactual Fine-Tuning for Locally Coherent and Targeted Image Synthesis. | Tian Xia, Matthew Sinclair, Andreas Schuh, Fabio De Sousa Ribeiro, Raghav Mehta, Rajat Rasal, Esther Puyol-Antn, Samuel Gerber, Kersten Petersen, Michiel Schaap, Ben Glocker |
| 2023 | MICCAI | 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 |
| 2023 | MICCAI | Exploring Compound Loss Functions for Brain Tumor Segmentation. | Anita Kriz, Raghav Mehta, Brennan Nichyporuk, Tal Arbel |
| 2023 | MICCAI | 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 |
| 2022 | MICCAI | Information Gain Sampling for Active Learning in Medical Image Classification. | Raghav Mehta, Changjian Shui, Brennan Nichyporuk, Tal Arbel |
| 2021 | MICCAI | 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 |
| 2019 | MICCAI | Improving Pathological Structure Segmentation via Transfer Learning Across Diseases. | Barleen Kaur, Paul Lematre, Raghav Mehta, Nazanin Mohammadi Sepahvand, Doina Precup, Douglas L. Arnold, Tal Arbel |
| 2019 | MICCAI | Propagating Uncertainty Across Cascaded Medical Imaging Tasks for Improved Deep Learning Inference. | Raghav Mehta, Thomas Christinck, Tanya Nair, Paul Lematre, Douglas L. Arnold, Tal Arbel |
| 2018 | MICCAI | To Learn or Not to Learn Features for Deformable Registration? | Aabhas Majumdar, Raghav Mehta, Jayanthi Sivaswamy |
| 2018 | MICCAI | RS-Net: Regression-Segmentation 3D CNN for Synthesis of Full Resolution Missing Brain MRI in the Presence of Tumours. | Raghav Mehta, Tal Arbel |
| 2018 | MICCAI | 3D U-Net for Brain Tumour Segmentation. | Raghav Mehta, Tal Arbel |