Brennan Nichyporuk

34 papers Journal 21Unranked 13

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Building a General SimCLR Self-Supervised Foundation Model Across Neurological Diseases to Advance 3D Brain MRI Diagnoses. ICCVW Emily Kaczmarek, Justin Szeto, Brennan Nichyporuk, Tal Arbel
2025	J	`jnl`	Building a General SimCLR Self-Supervised Foundation Model Across Neurological Diseases to Advance 3D Brain MRI Diagnoses. CoRR Emily Kaczmarek, Justin Szeto, Brennan Nichyporuk, Tal Arbel
2025	J	`jnl`	Conditional Diffusion Models are Medical Image Classifiers that Provide Explainability and Uncertainty for Free. CoRR Gian Mario Favero, Parham Saremi, Emily Kaczmarek, Brennan Nichyporuk, Tal Arbel
2025	J	`jnl`	Hyperfusion: A hypernetwork approach to multimodal integration of tabular and medical imaging data for predictive modeling. Medical Image Anal. Daniel Duenias, Brennan Nichyporuk, Tal Arbel, Tammy Riklin Raviv
2025	—	`conf`	Imagining Alternatives: Towards High-Resolution 3D Counterfactual Medical Image Generation via Language Guidance. ELAMI@MICCAI Mohamed Mohamed, Brennan Nichyporuk, Douglas L. Arnold, Tal Arbel
2025	J	`jnl`	Imagining Alternatives: Towards High-Resolution 3D Counterfactual Medical Image Generation via Language Guidance. CoRR Mohamed Mohamed, Brennan Nichyporuk, Douglas L. Arnold, Tal Arbel
2025	J	`jnl`	Improving Robustness and Reliability in Medical Image Classification With Latent-Guided Diffusion and Nested-Ensembles. IEEE Trans. Medical Imaging Xing Shen, Hengguan Huang, Brennan Nichyporuk, Tal Arbel
2025	J	`jnl`	SSL-AD: Spatiotemporal Self-Supervised Learning for Generalizability and Adaptability Across Alzheimer's Prediction Tasks and Datasets. CoRR Emily Kaczmarek, Justin Szeto, Brennan Nichyporuk, Tal Arbel
2025	—	`conf`	SSL-AD: Spatiotemporal Self-supervised Learning for Generalizability and Adaptability Across Alzheimer's Prediction Tasks and Datasets. LMID@MICCAI Emily Kaczmarek, Justin Szeto, Brennan Nichyporuk, Tal Arbel
2025	—	`conf`	Spatio-Temporal Conditional Diffusion Models for Forecasting Future Multiple Sclerosis Lesion Masks Conditioned on Treatments. LMID@MICCAI Gian Mario Favero, Ge Ya Luo, Nima Fathi, Justin Szeto, Douglas L. Arnold, Brennan Nichyporuk, Chris Pal, Tal Arbel
2025	J	`jnl`	Spatio-Temporal Conditional Diffusion Models for Forecasting Future Multiple Sclerosis Lesion Masks Conditioned on Treatments. CoRR Gian Mario Favero, Ge Ya Luo, Nima Fathi, Justin Szeto, Douglas L. Arnold, Brennan Nichyporuk, Chris Pal, Tal Arbel
2024	—	`conf`	DeCoDEx: Confounder Detector Guidance for Improved Diffusion-based Counterfactual Explanations. MIDL Nima Fathi, Amar Kumar, Brennan Nichyporuk, Mohammad Havaei, Tal Arbel
2024	J	`jnl`	DeCoDEx: Confounder Detector Guidance for Improved Diffusion-based Counterfactual Explanations. CoRR Nima Fathi, Amar Kumar, Brennan Nichyporuk, Mohammad Havaei, Tal Arbel
2024	J	`jnl`	HyperFusion: A Hypernetwork Approach to Multimodal Integration of Tabular and Medical Imaging Data for Predictive Modeling. CoRR Daniel Duenias, Brennan Nichyporuk, Tal Arbel, Tammy Riklin Raviv
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`	Exploring Compound Loss Functions for Brain Tumor Segmentation. BraTS/CrossMoDA@MICCAI Anita Kriz, Raghav Mehta, Brennan Nichyporuk, Tal Arbel
2023	J	`jnl`	Improving Robustness and Reliability in Medical Image Classification with Latent-Guided Diffusion and Nested-Ensembles. CoRR Xing Shen, Hengguan Huang, Brennan Nichyporuk, Tal Arbel
2023	J	`jnl`	Understanding metric-related pitfalls in image analysis validation. CoRR Annika Reinke, Minu Tizabi, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Carole H. Sudre, Laura Ación, Michela Antonelli, Tal Arbel, Spyridon Bakas, Arriel Benis, Matthew B. Blaschko, Florian Büttner, M. Jorge Cardoso, Veronika Cheplygina, Jianxu Chen, Evangelia Christodoulou, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Ben Glocker, Patrick Godau, Robert Haase, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Jens Kleesiek, Florian Kofler, Thijs Kooi, Annette Kopp-Schneider, Michal Kozubek, Anna Kreshuk, Tahsin M. Kurç, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus H. Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern H. Menze, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, Jens Petersen, Susanne M. Rafelski, Nasir M. Rajpoot, Mauricio Reyes, Michael A. Riegler, Nicola Rieke, Julio Saez-Rodriguez, Clara I. Sánchez, Shravya Shetty, Maarten van Smeden, Ronald M. Summers, Abdel A. Taha, Aleksei Tiulpin, Sotirios A. Tsaftaris, Ben Van Calster, Gaël Varoquaux, Manuel Wiesenfarth, Ziv R. Yaniv, Paul F. Jäger, Lena Maier-Hein
2022	—	`conf`	Counterfactual Image Synthesis for Discovery of Personalized Predictive Image Markers. AIIIMA/MIABID@MICCAI Amar Kumar, Anjun Hu, Brennan Nichyporuk, Jean-Pierre R. Falet, Douglas L. Arnold, Sotirios A. Tsaftaris, Tal Arbel
2022	J	`jnl`	Counterfactual Image Synthesis for Discovery of Personalized Predictive Image Markers. CoRR Amar Kumar, Anjun Hu, Brennan Nichyporuk, Jean-Pierre R. Falet, Douglas L. Arnold, Sotirios A. Tsaftaris, Tal Arbel
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`	Metrics reloaded: Pitfalls and recommendations for image analysis validation. CoRR Lena Maier-Hein, Annika Reinke, Evangelia Christodoulou, Ben Glocker, Patrick Godau, Fabian Isensee, Jens Kleesiek, Michal Kozubek, Mauricio Reyes, Michael A. Riegler, Manuel Wiesenfarth, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Minu Dietlinde Tizabi, Laura Ación, Michela Antonelli, Tal Arbel, Spyridon Bakas, Peter Bankhead, Arriel Benis, M. Jorge Cardoso, Veronika Cheplygina, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Bram van Ginneken, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Pierre Jannin, Charles E. Kahn, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Annette Kopp-Schneider, Anna Kreshuk, Tahsin M. Kurç, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus H. Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern H. Menze, David Moher, Karel G. M. Moons, Henning Müller, Felix Nickel, Brennan Nichyporuk, Jens Petersen, Nasir M. Rajpoot, Nicola Rieke, Julio Saez-Rodriguez, Clarisa Sánchez Gutiérrez, Shravya Shetty, Maarten van Smeden, Carole H. Sudre, Ronald M. Summers, Abdel A. Taha, Sotirios A. Tsaftaris, Ben Van Calster, Gaël Varoquaux, Paul F. Jäger
2022	—	`conf`	Personalized Prediction of Future Lesion Activity and Treatment Effect in Multiple Sclerosis from Baseline MRI. MIDL Joshua Durso-Finley, Jean-Pierre R. Falet, Brennan Nichyporuk, Douglas L. Arnold, Tal Arbel
2022	J	`jnl`	Personalized Prediction of Future Lesion Activity and Treatment Effect in Multiple Sclerosis from Baseline MRI. CoRR Joshua Durso-Finley, Jean-Pierre R. Falet, Brennan Nichyporuk, Douglas L. Arnold, 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
2021	—	`conf`	Accounting for Variance in Machine Learning Benchmarks. MLSys Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Nazanin Mohammadi Sepahvand, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Tal Arbel, Chris Pal, Gaël Varoquaux, Pascal Vincent
2021	J	`jnl`	Accounting for Variance in Machine Learning Benchmarks. CoRR Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Naz Sepah, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Dmitriy Serdyuk, Tal Arbel, Chris Pal, Gaël Varoquaux, Pascal Vincent
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`	Optimizing Operating Points for High Performance Lesion Detection and Segmentation Using Lesion Size Reweighting. CoRR Brennan Nichyporuk, Justin Szeto, Douglas L. Arnold, Tal Arbel