Raghav Mehta - RankMe

56 papers Journal 29Unranked 24

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Pixel-level Counterfactual Contrastive Learning for Medical Image Segmentation. CoRR Marceau Lafargue-Hauret, Raghav Mehta, Fabio De Sousa Ribeiro, Mélanie Roschewitz, Ben Glocker
2026	J	`jnl`	Positional Segmentor-Guided Counterfactual Fine-Tuning for Spatially Localized Image Synthesis. CoRR Tian Xia, Matthew Sinclair, Andreas Schuh, Fabio De Sousa Ribeiro, Raghav Mehta, Rajat Rasal, Esther Puyol-Antón, Samuel Gerber, Kersten Petersen, Michiel Schaap, Ben Glocker
2026	—	`ed.`	Uncertainty for Safe Utilization of Machine Learning in Medical Imaging - 7th International Workshop, UNSURE 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025, Proceedings UNSURE@MICCAI Carole H. Sudre, Mobarak I. Hoque, Raghav Mehta, Cheng Ouyang, Chen Qin, Marianne Rakic, William M. Wells
2025	—	`conf`	Automatic Dataset Shift Identification to Support Safe Deployment of Medical Imaging AI. MICCAI (7) Mélanie Roschewitz, Raghav Mehta, Charles Jones, Ben Glocker
2025	—	`conf`	CF-Seg: Counterfactuals Meet Segmentation. MICCAI (8) Raghav Mehta, Fabio De Sousa Ribeiro, Tian Xia, Mélanie Roschewitz, Ainkaran Santhirasekaram, Dominic C. Marshall, Ben Glocker
2025	J	`jnl`	CF-Seg: Counterfactuals meet Segmentation. CoRR Raghav Mehta, Fabio De Sousa Ribeiro, Tian Xia, Mélanie Roschewitz, Ainkaran Santhirasekaram, Dominic C. Marshall, Ben Glocker
2025	J	`jnl`	Cardiovascular disease classification using radiomics and geometric features from cardiac CT. CoRR Ajay Mittal, Raghav Mehta, Omar Todd, Philipp Seeböck, Georg Langs, Ben Glocker
2025	J	`jnl`	Decoupled Classifier-Free Guidance for Counterfactual Diffusion Models. CoRR Tian Xia, Fabio De Sousa Ribeiro, Rajat Rasal, Avinash Kori, Raghav Mehta, Ben Glocker
2025	—	`conf`	Delineation Uncertainty from Clinician Ranges in Cervical Cancer Radiotherapy Planning. ISIC@MICCAI Omar Todd, Sooha Kim, Katherine Mackay, Raghav Mehta, Fabio De Sousa Ribeiro, David Bernstein, Alexandra Taylor, Ben Glocker
2025	—	`conf`	Exploring the Interplay of Label Bias with Subgroup Size and Separability: A Case Study in Mammographic Density Classification. FAIMI@MICCAI Emma A. M. Stanley, Raghav Mehta, Mélanie Roschewitz, Nils D. Forkert, Ben Glocker
2025	J	`jnl`	Exploring the interplay of label bias with subgroup size and separability: A case study in mammographic density classification. CoRR Emma A. M. Stanley, Raghav Mehta, Mélanie Roschewitz, Nils D. Forkert, Ben Glocker
2025	J	`jnl`	Flow Stochastic Segmentation Networks. CoRR Fabio De Sousa Ribeiro, Omar Todd, Charles Jones, Avinash Kori, Raghav Mehta, Ben Glocker
2025	—	`conf`	Segmentor-Guided Counterfactual Fine-Tuning for Locally Coherent and Targeted Image Synthesis. MICCAI (2) Tian Xia, Matthew Sinclair, Andreas Schuh, Fabio De Sousa Ribeiro, Raghav Mehta, Rajat Rasal, Esther Puyol-Antón, Samuel Gerber, Kersten Petersen, Michiel Schaap, Ben Glocker
2025	J	`jnl`	Segmentor-Guided Counterfactual Fine-Tuning for Locally Coherent and Targeted Image Synthesis. CoRR Tian Xia, Matthew Sinclair, Andreas Schuh, Fabio De Sousa Ribeiro, Raghav Mehta, Rajat Rasal, Esther Puyol-Antón, Samuel Gerber, Kersten Petersen, Michiel Schaap, Ben Glocker
2025	—	`conf`	UNSURF: Uncertainty Quantification for Cortical Surface Reconstruction of Clinical Brain MRIs. MICCAI (16) Karthik Gopinath, Raghav Mehta, Ben Glocker, Juan Eugenio Iglesias
2025	J	`jnl`	UNSURF: Uncertainty Quantification for Cortical Surface Reconstruction of Clinical Brain MRIs. CoRR Raghav Mehta, Karthik Gopinath, Ben Glocker, Juan Eugenio Iglesias
2025	—	`ed.`	Uncertainty for Safe Utilization of Machine Learning in Medical Imaging - 6th International Workshop, UNSURE 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings UNSURE@MICCAI Carole H. Sudre, Raghav Mehta, Cheng Ouyang, Chen Qin, Marianne Rakic, William M. Wells III
2025	J	`jnl`	Where are we with calibration under dataset shift in image classification? CoRR Mélanie Roschewitz, Raghav Mehta, Fabio De Sousa Ribeiro, Ben Glocker
2025	J	`jnl`	Where are we with calibration under dataset shift in image classification? Trans. Mach. Learn. Res. Mélanie Roschewitz, Raghav Mehta, Fabio De Sousa Ribeiro, Ben Glocker
2024	J	`jnl`	Automatic dataset shift identification to support root cause analysis of AI performance drift. CoRR Mélanie Roschewitz, Raghav Mehta, Charles Jones, Ben Glocker
2023	—	`conf`	Confusing Large Models by Confusing Small Models. ICCV (Workshops) Vítor Albiero, Raghav Mehta, Ivan Evtimov, Samuel J. Bell, Levent Sagun, Aram Markosyan
2023	J	`jnl`	Debiasing Counterfactuals In the Presence of Spurious Correlations. CoRR Amar Kumar, Nima Fathi, Raghav Mehta, Brennan Nichyporuk, Jean-Pierre R. Falet, Sotirios A. Tsaftaris, Tal Arbel
2023	—	`conf`	Debiasing Counterfactuals in the Presence of Spurious Correlations. CLIP/FAIMI/EPIMI@MICCAI Amar Kumar, Nima Fathi, Raghav Mehta, Brennan Nichyporuk, Jean-Pierre R. Falet, Sotirios A. Tsaftaris, Tal Arbel
2023	—	`conf`	Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis. MIDL Raghav Mehta, Changjian Shui, Tal Arbel
2023	J	`jnl`	Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis. CoRR Raghav Mehta, Changjian Shui, Tal Arbel
2023	—	`conf`	Exploring Compound Loss Functions for Brain Tumor Segmentation. BraTS/CrossMoDA@MICCAI Anita Kriz, Raghav Mehta, Brennan Nichyporuk, Tal Arbel
2023	—	`conf`	Improving Image-Based Precision Medicine with Uncertainty-Aware Causal Models. MICCAI (5) Joshua Durso-Finley, Jean-Pierre R. Falet, Raghav Mehta, Douglas L. Arnold, Nick Pawlowski, Tal Arbel
2023	J	`jnl`	Improving Image-Based Precision Medicine with Uncertainty-Aware Causal Models. CoRR Joshua Durso-Finley, Jean-Pierre R. Falet, Raghav Mehta, Douglas L. Arnold, Nick Pawlowski, Tal Arbel
2023	—	`conf`	Mitigating Calibration Bias Without Fixed Attribute Grouping for Improved Fairness in Medical Imaging Analysis. MICCAI (3) Changjian Shui, Justin Szeto, Raghav Mehta, Douglas L. Arnold, Tal Arbel
2023	J	`jnl`	Mitigating Calibration Bias Without Fixed Attribute Grouping for Improved Fairness in Medical Imaging Analysis. CoRR Changjian Shui, Justin Szeto, Raghav Mehta, Douglas L. Arnold, Tal Arbel
2023	—	`ed.`	Uncertainty for Safe Utilization of Machine Learning in Medical Imaging - 5th International Workshop, UNSURE 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings UNSURE@MICCAI Carole H. Sudre, Christian F. Baumgartner, Adrian V. Dalca, Raghav Mehta, Chen Qin, William M. Wells III
2022	—	`conf`	Information Gain Sampling for Active Learning in Medical Image Classification. UNSURE@MICCAI Raghav Mehta, Changjian Shui, Brennan Nichyporuk, Tal Arbel
2022	J	`jnl`	Information Gain Sampling for Active Learning in Medical Image Classification. CoRR Raghav Mehta, Changjian Shui, Brennan Nichyporuk, Tal Arbel
2022	J	`jnl`	Propagating Uncertainty Across Cascaded Medical Imaging Tasks for Improved Deep Learning Inference. IEEE Trans. Medical Imaging Raghav Mehta, Thomas Christinck, Tanya Nair, Aurélie Bussy, Swapna Premasiri, Manuela Costantino, M. Mallar Chakravarthy, Douglas L. Arnold, Yarin Gal, Tal Arbel
2022	J	`jnl`	Rethinking Generalization: The Impact of Annotation Style on Medical Image Segmentation. CoRR Brennan Nichyporuk, Jillian Cardinell, Justin Szeto, Raghav Mehta, Jean-Pierre R. Falet, Douglas L. Arnold, Sotirios A. Tsaftaris, Tal Arbel
2022	J	`jnl`	You Only Need a Good Embeddings Extractor to Fix Spurious Correlations. CoRR Raghav Mehta, Vítor Albiero, Li Chen, Ivan Evtimov, Tamar Glaser, Zhiheng Li, Tal Hassner
2021	—	`conf`	Cohort Bias Adaptation in Aggregated Datasets for Lesion Segmentation. DART/FAIR@MICCAI Brennan Nichyporuk, Jillian Cardinell, Justin Szeto, Raghav Mehta, Sotirios A. Tsaftaris, Douglas L. Arnold, Tal Arbel
2021	J	`jnl`	Cohort Bias Adaptation in Aggregated Datasets for Lesion Segmentation. CoRR Brennan Nichyporuk, Jillian Cardinell, Justin Szeto, Raghav Mehta, Sotirios A. Tsaftaris, Douglas L. Arnold, Tal Arbel
2021	—	`conf`	HAD-Net: A Hierarchical Adversarial Knowledge Distillation Network for Improved Enhanced Tumour Segmentation Without Post-Contrast Images. MIDL Saverio Vadacchino, Raghav Mehta, Nazanin Mohammadi Sepahvand, Brennan Nichyporuk, James J. Clark, Tal Arbel
2021	J	`jnl`	HAD-Net: A Hierarchical Adversarial Knowledge Distillation Network for Improved Enhanced Tumour Segmentation Without Post-Contrast Images. CoRR Saverio Vadacchino, Raghav Mehta, Nazanin Mohammadi Sepahvand, Brennan Nichyporuk, James J. Clark, Tal Arbel
2021	J	`jnl`	QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results. CoRR 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, Benjamin C. Wagner, Fang F. Yu, Baowei Fei, Ananth J. Madhuranthakam, Joseph A. Maldjian, Laura Alexandra Daza, Catalina Gómez Caballero, Pablo Arbeláez, Chengliang Dai, Shuo Wang, Hadrien Raynaud, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai, Subhashis Banerjee, Linmin Pei, Murat Ak, Sarahi Rosas-González, Ilyess Zemmoura, Clovis Tauber, Minh H. Vu, Tufve Nyholm, Tommy Löfstedt, Laura Mora Ballestar, Verónica Vilaplana, Hugh McHugh, Gonzalo D. Maso Talou, Alan Wang, Jay B. Patel, Ken Chang, Katharina Hoebel, Mishka Gidwani, Nishanth Thumbavanam Arun, Sharut Gupta, Mehak Aggarwal, Praveer Singh, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer, Nicolas Boutry, Alexis Huard, Lasitha Vidyaratne, Md Monibor Rahman, Khan M. Iftekharuddin, Joseph Chazalon, Élodie Puybareau, Guillaume Tochon, Jun Ma, Mariano Cabezas, Xavier Lladó, Arnau Oliver, Liliana Valencia, Sergi Valverde, Mehdi Amian, Mohammadreza Soltaninejad, Andriy Myronenko, Ali Hatamizadeh, Xue Feng, Quan Dou, Nicholas J. Tustison, Craig H. Meyer, Nisarg A. Shah, Sanjay N. Talbar, Marc-André Weber, Abhishek Mahajan, András Jakab, Roland Wiest, Hassan M. Fathallah-Shaykh, Arash Nazeri, Mikhail Milchenko, Daniel S. Marcus, Aikaterini Kotrotsou, Rivka Colen, John B. Freymann, Justin S. Kirby, Christos Davatzikos, Bjoern H. Menze, Spyridon Bakas, Yarin Gal, Tal Arbel
2021	J	`jnl`	Sub-cortical structure segmentation database for young population. CoRR Jayanthi Sivaswamy, Alphin J. Thottupattu, Mythri V, Raghav Mehta, R. Sheelakumari, Chandrasekharan Kesavadas
2020	J	`jnl`	Uncertainty Evaluation Metric for Brain Tumour Segmentation. CoRR Raghav Mehta, Angelos Filos, Yarin Gal, Tal Arbel
2019	J	`jnl`	Hybrid Cell Assignment and Sizing for Power, Area, Delay Product Optimization of SRAM Arrays. CoRR Ghasem Pasandi, Raghav Mehta, Massoud Pedram, Shahin Nazarian
2019	J	`jnl`	Hybrid Cell Assignment and Sizing for Power, Area, Delay-Product Optimization of SRAM Arrays. IEEE Trans. Circuits Syst. II Express Briefs Ghasem Pasandi, Raghav Mehta, Massoud Pedram, Shahin Nazarian
2019	—	`conf`	Improving Pathological Structure Segmentation via Transfer Learning Across Diseases. DART/MIL3ID@MICCAI Barleen Kaur, Paul Lemaître, Raghav Mehta, Nazanin Mohammadi Sepahvand, Doina Precup, Douglas L. Arnold, Tal Arbel
2019	—	`conf`	NormCo: Deep Disease Normalization for Biomedical Knowledge Base Construction. AKBC Dustin Wright, Yannis Katsis, Raghav Mehta, Chun-Nan Hsu
2019	—	`conf`	Propagating Uncertainty Across Cascaded Medical Imaging Tasks for Improved Deep Learning Inference. UNSURE/CLIP@MICCAI Raghav Mehta, Thomas Christinck, Tanya Nair, Paul Lemaître, Douglas L. Arnold, Tal Arbel
2018	—	`conf`	3D U-Net for Brain Tumour Segmentation. BrainLes@MICCAI (2) Raghav Mehta, Tal Arbel
2018	—	`conf`	High performance training of deep neural networks using pipelined hardware acceleration and distributed memory. ISQED Raghav Mehta, Yuyang Huang, Mingxi Cheng, Shrey Bagga, Nishant Mathur, Ji Li, Jeffrey Draper, Shahin Nazarian
2018	—	`conf`	RS-Net: Regression-Segmentation 3D CNN for Synthesis of Full Resolution Missing Brain MRI in the Presence of Tumours. SASHIMI@MICCAI Raghav Mehta, Tal Arbel
2018	J	`jnl`	RS-Net: Regression-Segmentation 3D CNN for Synthesis of Full Resolution Missing Brain MRI in the Presence of Tumours. CoRR Raghav Mehta, Tal Arbel
2018	—	`conf`	To Learn or Not to Learn Features for Deformable Registration? MLCN/DLF/iMIMIC@MICCAI Aabhas Majumdar, Raghav Mehta, Jayanthi Sivaswamy
2017	—	`conf`	M-net: A Convolutional Neural Network for deep brain structure segmentation. ISBI Raghav Mehta, Jayanthi Sivaswamy
2017	J	`jnl`	To Learn or Not to Learn Features for Deformable Registration? CoRR Aabhas Majumdar, Raghav Mehta, Jayanthi Sivaswamy
2016	—	`conf`	A hybrid approach to tissue-based intensity standardization of brain MRI images. ISBI Raghav Mehta, Jayanthi Sivaswamy