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- affiliation: McGill University, Canada
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2020 – today
- 2024
[i37]Daniel Duenias, Brennan Nichyporuk, Tal Arbel, Tammy Riklin Raviv:
HyperFusion: A Hypernetwork Approach to Multimodal Integration of Tabular and Medical Imaging Data for Predictive Modeling. CoRR abs/2403.13319 (2024)- [i36]Nima Fathi, Amar Kumar, Brennan Nichyporuk, Mohammad Havaei, Tal Arbel:
DeCoDEx: Confounder Detector Guidance for Improved Diffusion-based Counterfactual Explanations. CoRR abs/2405.09288 (2024) - [i35]Joshua Durso-Finley, Berardino Barile, Jean-Pierre R. Falet, Douglas L. Arnold, Nick Pawlowski, Tal Arbel:
Probabilistic Temporal Prediction of Continuous Disease Trajectories and Treatment Effects Using Neural SDEs. CoRR abs/2406.12807 (2024) - 2023
- [j36]Qing Tian
, Tal Arbel, James J. Clark:
Grow-push-prune: Aligning deep discriminants for effective structural network compression. Comput. Vis. Image Underst. 231: 103682 (2023) - [c78]Amar Kumar, Nima Fathi, Raghav Mehta, Brennan Nichyporuk, Jean-Pierre R. Falet, Sotirios A. Tsaftaris, Tal Arbel:
Debiasing Counterfactuals in the Presence of Spurious Correlations. CLIP/FAIMI/EPIMI@MICCAI 2023: 276-286 - [c77]Changjian Shui, Justin Szeto, Raghav Mehta, Douglas L. Arnold, Tal Arbel:
Mitigating Calibration Bias Without Fixed Attribute Grouping for Improved Fairness in Medical Imaging Analysis. MICCAI (3) 2023: 189-198 - [c76]Joshua Durso-Finley, Jean-Pierre R. Falet, Raghav Mehta, Douglas L. Arnold, Nick Pawlowski, Tal Arbel:
Improving Image-Based Precision Medicine with Uncertainty-Aware Causal Models. MICCAI (5) 2023: 472-481 - [c75]Raghav Mehta, Changjian Shui, Tal Arbel:
Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis. MIDL 2023: 1453-1492 - [i34]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:
Understanding metric-related pitfalls in image analysis validation. CoRR abs/2302.01790 (2023) - [i33]Raghav Mehta, Changjian Shui, Tal Arbel:
Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis. CoRR abs/2303.03242 (2023) - [i32]Junde Wu, Rao Fu, Huihui Fang, Yuanpei Liu, Zhaowei Wang, Yanwu Xu, Yueming Jin, Tal Arbel:
Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation. CoRR abs/2304.12620 (2023) - [i31]Joshua Durso-Finley, Jean-Pierre R. Falet, Raghav Mehta, Douglas L. Arnold, Nick Pawlowski, Tal Arbel:
Improving Image-Based Precision Medicine with Uncertainty-Aware Causal Models. CoRR abs/2305.03829 (2023) - [i30]Changjian Shui, Justin Szeto, Raghav Mehta, Douglas L. Arnold, Tal Arbel:
Mitigating Calibration Bias Without Fixed Attribute Grouping for Improved Fairness in Medical Imaging Analysis. CoRR abs/2307.01738 (2023) - [i29]Amar Kumar, Nima Fathi, Raghav Mehta, Brennan Nichyporuk, Jean-Pierre R. Falet, Sotirios A. Tsaftaris, Tal Arbel:
Debiasing Counterfactuals In the Presence of Spurious Correlations. CoRR abs/2308.10984 (2023) - [i28]Xing Shen, Hengguan Huang, Brennan Nichyporuk, Tal Arbel:
Improving Robustness and Reliability in Medical Image Classification with Latent-Guided Diffusion and Nested-Ensembles. CoRR abs/2310.15952 (2023) - 2022
- [j35]Raghav Mehta, Thomas Christinck, Tanya Nair, Aurélie Bussy, Swapna Premasiri, Manuela Costantino, M. Mallar Chakravarthy, Douglas L. Arnold, Yarin Gal, Tal Arbel:
Propagating Uncertainty Across Cascaded Medical Imaging Tasks for Improved Deep Learning Inference. IEEE Trans. Medical Imaging 41(2): 360-373 (2022) - [c74]Chelsea Myers-Colet, Julien Schroeter, Douglas L. Arnold, Tal Arbel:
Heatmap Regression for Lesion Detection Using Pointwise Annotations. MILLanD@MICCAI 2022: 3-12 - [c73]Amar Kumar, Anjun Hu, Brennan Nichyporuk, Jean-Pierre R. Falet, Douglas L. Arnold, Sotirios A. Tsaftaris, Tal Arbel:
Counterfactual Image Synthesis for Discovery of Personalized Predictive Image Markers. AIIIMA/MIABID@MICCAI 2022: 113-124 - [c72]Raghav Mehta, Changjian Shui, Brennan Nichyporuk, Tal Arbel:
Information Gain Sampling for Active Learning in Medical Image Classification. UNSURE@MICCAI 2022: 135-145 - [c71]Joshua Durso-Finley, Jean-Pierre R. Falet, Brennan Nichyporuk, Douglas L. Arnold, Tal Arbel:
Personalized Prediction of Future Lesion Activity and Treatment Effect in Multiple Sclerosis from Baseline MRI. MIDL 2022: 387-406 - [c70]Julien Schroeter, Chelsea Myers-Colet, Douglas L. Arnold, Tal Arbel:
Segmentation-Consistent Probabilistic Lesion Counting. MIDL 2022: 1034-1056 - [c69]Changjian Shui, Gezheng Xu, Qi Chen, Jiaqi Li, Charles X. Ling, Tal Arbel, Boyu Wang, Christian Gagné:
On Learning Fairness and Accuracy on Multiple Subgroups. NeurIPS 2022 - [i27]Joshua Durso-Finley, Jean-Pierre R. Falet, Brennan Nichyporuk, Douglas L. Arnold, Tal Arbel:
Personalized Prediction of Future Lesion Activity and Treatment Effect in Multiple Sclerosis from Baseline MRI. CoRR abs/2204.01702 (2022) - [i26]Julien Schroeter, Chelsea Myers-Colet, Douglas L. Arnold, Tal Arbel:
Segmentation-Consistent Probabilistic Lesion Counting. CoRR abs/2204.05276 (2022) - [i25]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:
Metrics reloaded: Pitfalls and recommendations for image analysis validation. CoRR abs/2206.01653 (2022) - [i24]Raghav Mehta, Changjian Shui, Brennan Nichyporuk, Tal Arbel:
Information Gain Sampling for Active Learning in Medical Image Classification. CoRR abs/2208.00974 (2022) - [i23]Amar Kumar, Anjun Hu, Brennan Nichyporuk, Jean-Pierre R. Falet, Douglas L. Arnold, Sotirios A. Tsaftaris, Tal Arbel:
Counterfactual Image Synthesis for Discovery of Personalized Predictive Image Markers. CoRR abs/2208.02311 (2022) - [i22]Chelsea Myers-Colet, Julien Schroeter, Douglas L. Arnold, Tal Arbel:
Heatmap Regression for Lesion Detection using Pointwise Annotations. CoRR abs/2208.05939 (2022) - [i21]Changjian Shui, Gezheng Xu, Qi Chen, Jiaqi Li, Charles Ling, Tal Arbel, Boyu Wang, Christian Gagné:
On Learning Fairness and Accuracy on Multiple Subgroups. CoRR abs/2210.10837 (2022) - [i20]Brennan Nichyporuk, Jillian Cardinell, Justin Szeto, Raghav Mehta, Jean-Pierre R. Falet, Douglas L. Arnold, Sotirios A. Tsaftaris, Tal Arbel:
Rethinking Generalization: The Impact of Annotation Style on Medical Image Segmentation. CoRR abs/2210.17398 (2022) - [i19]Anjun Hu, Jean-Pierre R. Falet, Brennan S. Nichyporuk, Changjian Shui, Douglas L. Arnold, Sotirios A. Tsaftaris, Tal Arbel:
Clinically Plausible Pathology-Anatomy Disentanglement in Patient Brain MRI with Structured Variational Priors. CoRR abs/2211.07820 (2022) - 2021
- [j34]Qing Tian, Tal Arbel, James J. Clark:
Task dependent deep LDA pruning of neural networks. Comput. Vis. Image Underst. 203: 103154 (2021) - [c68]Brennan Nichyporuk, Jillian Cardinell, Justin Szeto, Raghav Mehta, Sotirios A. Tsaftaris, Douglas L. Arnold, Tal Arbel:
Cohort Bias Adaptation in Aggregated Datasets for Lesion Segmentation. DART/FAIR@MICCAI 2021: 101-111 - [c67]Saverio Vadacchino, Raghav Mehta, Nazanin Mohammadi Sepahvand, Brennan Nichyporuk, James J. Clark, Tal Arbel:
HAD-Net: A Hierarchical Adversarial Knowledge Distillation Network for Improved Enhanced Tumour Segmentation Without Post-Contrast Images. MIDL 2021: 787-801 - [c66]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:
Accounting for Variance in Machine Learning Benchmarks. MLSys 2021 - [i18]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:
Accounting for Variance in Machine Learning Benchmarks. CoRR abs/2103.03098 (2021) - [i17]Saverio Vadacchino, Raghav Mehta, Nazanin Mohammadi Sepahvand, Brennan Nichyporuk, James J. Clark, Tal Arbel:
HAD-Net: A Hierarchical Adversarial Knowledge Distillation Network for Improved Enhanced Tumour Segmentation Without Post-Contrast Images. CoRR abs/2103.16617 (2021) - [i16]Annika Reinke, Matthias Eisenmann, Minu Dietlinde Tizabi, Carole H. Sudre, Tim Rädsch, Michela Antonelli, Tal Arbel, Spyridon Bakas, M. Jorge Cardoso, Veronika Cheplygina, Keyvan Farahani, Ben Glocker, Doreen Heckmann-Nötzel, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Jens Kleesiek, Tahsin M. Kurç, Michal Kozubek, Bennett A. Landman, Geert Litjens, Klaus H. Maier-Hein, Bjoern H. Menze, Henning Müller, Jens Petersen, Mauricio Reyes, Nicola Rieke, Bram Stieltjes, Ronald M. Summers, Sotirios A. Tsaftaris, Bram van Ginneken, Annette Kopp-Schneider, Paul Jäger, Lena Maier-Hein:
Common Limitations of Image Processing Metrics: A Picture Story. CoRR abs/2104.05642 (2021) - [i15]Brennan Nichyporuk, Justin Szeto, Douglas L. Arnold, Tal Arbel:
Optimizing Operating Points for High Performance Lesion Detection and Segmentation Using Lesion Size Reweighting. CoRR abs/2107.12978 (2021) - [i14]Brennan Nichyporuk, Jillian Cardinell, Justin Szeto, Raghav Mehta, Sotirios A. Tsaftaris, Douglas L. Arnold, Tal Arbel:
Cohort Bias Adaptation in Aggregated Datasets for Lesion Segmentation. CoRR abs/2108.00713 (2021) - [i13]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:
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results. CoRR abs/2112.10074 (2021) - 2020
- [j33]Tanya Nair, Doina Precup, Douglas L. Arnold, Tal Arbel:
Exploring uncertainty measures in deep networks for Multiple sclerosis lesion detection and segmentation. Medical Image Anal. 59 (2020) - [j32]Lena Maier-Hein, Annika Reinke, Michal Kozubek, Anne L. Martel, Tal Arbel, Matthias Eisenmann, Allan Hanbury, Pierre Jannin, Henning Müller, Sinan Onogur, Julio Saez-Rodriguez, Bram van Ginneken, Annette Kopp-Schneider, Bennett A. Landman:
BIAS: Transparent reporting of biomedical image analysis challenges. Medical Image Anal. 66: 101796 (2020) - [c65]Nazanin Mohammadi Sepahvand, Douglas L. Arnold, Tal Arbel:
CNN Detection of New and Enlarging Multiple Sclerosis Lesions from Longitudinal Mri Using Subtraction Images. ISBI 2020: 127-130 - [e12]Carole H. Sudre, Hamid Fehri, Tal Arbel, Christian F. Baumgartner, Adrian V. Dalca, Ryutaro Tanno, Koen Van Leemput, William M. Wells III, Aristeidis Sotiras, Bartlomiej W. Papiez, Enzo Ferrante, Sarah Parisot:
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis - Second International Workshop, UNSURE 2020, and Third International Workshop, GRAIL 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings. Lecture Notes in Computer Science 12443, Springer 2020, ISBN 978-3-030-60364-9 [contents] - [e11]Tal Arbel, Ismail Ben Ayed, Marleen de Bruijne, Maxime Descoteaux, Hervé Lombaert, Christopher Pal:
International Conference on Medical Imaging with Deep Learning, MIDL 2020, 6-8 July 2020, Montréal, QC, Canada. Proceedings of Machine Learning Research 121, PMLR 2020 [contents] - [i12]Raghav Mehta, Angelos Filos, Yarin Gal, Tal Arbel:
Uncertainty Evaluation Metric for Brain Tumour Segmentation. CoRR abs/2005.14262 (2020) - [i11]Tal Arbel, Ismail Ben Ayed, Marleen de Bruijne, Maxime Descoteaux, Herve Lombaert, Chris Pal:
Medical Imaging with Deep Learning: MIDL 2020 - Short Paper Track. CoRR abs/2007.02319 (2020) - [i10]Qing Tian, Tal Arbel, James J. Clark:
Deep discriminant analysis for task-dependent compact network search. CoRR abs/2009.13716 (2020) - [i9]Boris N. Oreshkin, Tal Arbel:
Uncertainty driven probabilistic voxel selection for image registration. CoRR abs/2010.00988 (2020) - [i8]Boris N. Oreshkin, Tal Arbel:
Optimization over Random and Gradient Probabilistic Pixel Sampling for Fast, Robust Multi-Resolution Image Registration. CoRR abs/2010.02505 (2020)
2010 – 2019
- 2019
- [c64]Joshua Durso-Finley, Douglas L. Arnold, Tal Arbel:
Saliency Based Deep Neural Network for Automatic Detection of Gadolinium-Enhancing Multiple Sclerosis Lesions in Brain MRI. BrainLes@MICCAI (1) 2019: 108-118 - [c63]Raghav Mehta, Thomas Christinck, Tanya Nair, Paul Lemaître, Douglas L. Arnold, Tal Arbel:
Propagating Uncertainty Across Cascaded Medical Imaging Tasks for Improved Deep Learning Inference. UNSURE/CLIP@MICCAI 2019: 23-32 - [c62]Barleen Kaur, Paul Lemaître, Raghav Mehta, Nazanin Mohammadi Sepahvand, Doina Precup, Douglas L. Arnold, Tal Arbel:
Improving Pathological Structure Segmentation via Transfer Learning Across Diseases. DART/MIL3ID@MICCAI 2019: 90-98 - [c61]Adrian Tousignant, Paul Lemaître, Doina Precup, Douglas L. Arnold, Tal Arbel:
Prediction of Disease Progression in Multiple Sclerosis Patients using Deep Learning Analysis of MRI Data. MIDL 2019: 483-492 - [e10]Hayit Greenspan, Ryutaro Tanno, Marius Erdt, Tal Arbel, Christian F. Baumgartner, Adrian V. Dalca, Carole H. Sudre, William M. Wells III, Klaus Drechsler, Marius George Linguraru, Cristina Oyarzun Laura, Raj Shekhar, Stefan Wesarg, Miguel Ángel González Ballester:
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures - First International Workshop, UNSURE 2019, and 8th International Workshop, CLIP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings. Lecture Notes in Computer Science 11840, Springer 2019, ISBN 978-3-030-32688-3 [contents] - [i7]Lena Maier-Hein, Annika Reinke, Michal Kozubek, Anne L. Martel, Tal Arbel, Matthias Eisenmann, Allan Hanbury, Pierre Jannin, Henning Müller, Sinan Onogur, Julio Saez-Rodriguez, Bram van Ginneken, Annette Kopp-Schneider, Bennett A. Landman:
BIAS: Transparent reporting of biomedical image analysis challenges. CoRR abs/1910.04071 (2019) - 2018
- [j31]Qing Tian, Tal Arbel, James J. Clark:
Structured deep Fisher pruning for efficient facial trait classification. Image Vis. Comput. 77: 45-59 (2018) - [c60]Nazanin Mohammadi Sepahvand, Tal Hassner, Douglas L. Arnold, Tal Arbel:
CNN Prediction of Future Disease Activity for Multiple Sclerosis Patients from Baseline MRI and Lesion Labels. BrainLes@MICCAI (1) 2018: 57-69 - [c59]Raghav Mehta, Tal Arbel:
RS-Net: Regression-Segmentation 3D CNN for Synthesis of Full Resolution Missing Brain MRI in the Presence of Tumours. SASHIMI@MICCAI 2018: 119-129 - [c58]Raghav Mehta, Tal Arbel:
3D U-Net for Brain Tumour Segmentation. BrainLes@MICCAI (2) 2018: 254-266 - [c57]Annika Reinke, Matthias Eisenmann, Sinan Onogur, Marko Stankovic, Patrick Scholz, Peter M. Full, Hrvoje Bogunovic, Bennett A. Landman, Oskar Maier, Bjoern H. Menze, Gregory C. Sharp, Korsuk Sirinukunwattana, Stefanie Speidel, Fons van der Sommen, Guoyan Zheng, Henning Müller, Michal Kozubek, Tal Arbel, Andrew P. Bradley, Pierre Jannin, Annette Kopp-Schneider, Lena Maier-Hein:
How to Exploit Weaknesses in Biomedical Challenge Design and Organization. MICCAI (4) 2018: 388-395 - [c56]Tanya Nair, Doina Precup, Douglas L. Arnold, Tal Arbel:
Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis Lesion Detection and Segmentation. MICCAI (1) 2018: 655-663 - [i6]Qing Tian, Tal Arbel, James J. Clark:
Fisher Pruning of Deep Nets for Facial Trait Classification. CoRR abs/1803.08134 (2018) - [i5]Lena Maier-Hein, Matthias Eisenmann, Annika Reinke, Sinan Onogur, Marko Stankovic, Patrick Scholz, Tal Arbel, Hrvoje Bogunovic, Andrew P. Bradley, Aaron Carass, Carolin Feldmann, Alejandro F. Frangi, Peter M. Full, Bram van Ginneken, Allan Hanbury, Katrin Honauer, Michal Kozubek, Bennett A. Landman, Keno März, Oskar Maier, Klaus H. Maier-Hein, Bjoern H. Menze, Henning Müller, Peter F. Neher, Wiro J. Niessen, Nasir M. Rajpoot, Gregory C. Sharp, Korsuk Sirinukunwattana, Stefanie Speidel, Christian Stock, Danail Stoyanov, Abdel Aziz Taha, Fons van der Sommen, Ching-Wei Wang, Marc-André Weber, Guoyan Zheng, Pierre Jannin, Annette Kopp-Schneider:
Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions. CoRR abs/1806.02051 (2018) - [i4]Raghav Mehta, Tal Arbel:
RS-Net: Regression-Segmentation 3D CNN for Synthesis of Full Resolution Missing Brain MRI in the Presence of Tumours. CoRR abs/1807.10972 (2018) - [i3]Tanya Nair, Doina Precup, Douglas L. Arnold, Tal Arbel:
Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis Lesion Detection and Segmentation. CoRR abs/1808.01200 (2018) - [i2]Spyridon Bakas, Mauricio Reyes, András Jakab, Stefan Bauer, Markus Rempfler, Alessandro Crimi, Russell Takeshi Shinohara, Christoph Berger, Sung Min Ha, Martin Rozycki, Marcel Prastawa, Esther Alberts, Jana Lipková, John B. Freymann, Justin S. Kirby, Michel Bilello, Hassan M. Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Benedikt Wiestler, Rivka R. Colen, Aikaterini Kotrotsou, Pamela LaMontagne, Daniel S. Marcus, Mikhail Milchenko, Arash Nazeri, Marc-André Weber, Abhishek Mahajan, Ujjwal Baid, Dongjin Kwon, Manu Agarwal, Mahbubul Alam, Alberto Albiol, Antonio Albiol, Alex Varghese, Tran Anh Tuan, Tal Arbel, Aaron Avery, Pranjal B., Subhashis Banerjee, Thomas Batchelder, Kayhan N. Batmanghelich, Enzo Battistella, Martin Bendszus, Eze Benson, José Bernal, George Biros, Mariano Cabezas, Siddhartha Chandra, Yi-Ju Chang, et al.:
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge. CoRR abs/1811.02629 (2018) - 2017
- [j30]Simon Drouin, Anna Kochanowska, Marta Kersten-Oertel, Ian J. Gerard, Rina Zelmann, Dante De Nigris, Silvain Bériault, Tal Arbel, Denis Sirhan, Abbas F. Sadikot, Jeffery A. Hall, David S. Sinclair, Kevin Petrecca, Rolando F. DelMaestro, D. Louis Collins:
IBIS: an OR ready open-source platform for image-guided neurosurgery. Int. J. Comput. Assist. Radiol. Surg. 12(3): 363-378 (2017) - [c55]Qing Tian, Tal Arbel, James J. Clark:
Deep LDA-Pruned Nets for Efficient Facial Gender Classification. CVPR Workshops 2017: 512-521 - [c54]Andrew Doyle, Colm Elliott, Zahra Karimaghaloo, Nagesh K. Subbanna, Douglas L. Arnold, Tal Arbel:
Lesion Detection, Segmentation and Prediction in Multiple Sclerosis Clinical Trials. BrainLes@MICCAI 2017: 15-28 - [c53]Andrew Doyle, Doina Precup, Douglas L. Arnold, Tal Arbel:
Predicting Future Disease Activity and Treatment Responders for Multiple Sclerosis Patients Using a Bag-of-Lesions Brain Representation. MICCAI (3) 2017: 186-194 - [c52]Andrew Jesson, Tal Arbel:
Brain Tumor Segmentation Using a 3D FCN with Multi-scale Loss. BrainLes@MICCAI 2017: 392-402 - [e9]Henning Müller, B. Michael Kelm, Tal Arbel, Weidong Cai, Manual Jorge Cardoso, Georg Langs, Bjoern H. Menze, Dimitris N. Metaxas, Albert Montillo, William M. Wells III, Shaoting Zhang, Albert C. S. Chung, Mark Jenkinson, Annemie Ribbens:
Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging - MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers. Lecture Notes in Computer Science 10081, Springer 2017, ISBN 978-3-319-61187-7 [contents] - [e8]M. Jorge Cardoso, Tal Arbel, João Manuel R. S. Tavares, Stephen R. Aylward, Shuo Li, Emad Boctor, Gabor Fichtinger, Kevin Cleary, Bradley Freeman, Luv Kohli, Deborah Shipley Kane, Matt Oetgen, Sonja Pujol:
Imaging for Patient-Customized Simulations and Systems for Point-of-Care Ultrasound - International Workshops, BIVPCS 2017 and POCUS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, 2017, Proceedings. Lecture Notes in Computer Science 10549, Springer 2017, ISBN 978-3-319-67551-0 [contents] - [e7]M. Jorge Cardoso, Tal Arbel, Xiongbiao Luo, Stefan Wesarg, Tobias Reichl, Miguel Ángel González Ballester, A. Jonathan McLeod, Klaus Drechsler, Terry M. Peters, Marius Erdt, Kensaku Mori, Marius George Linguraru, Andreas Uhl, Cristina Oyarzun Laura, Raj Shekhar:
Computer Assisted and Robotic Endoscopy and Clinical Image-Based Procedures - 4th International Workshop, CARE 2017, and 6th International Workshop, CLIP 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, 2017, Proceedings. Lecture Notes in Computer Science 10550, Springer 2017, ISBN 978-3-319-67542-8 [contents] - [e6]M. Jorge Cardoso, Tal Arbel, Enzo Ferrante, Xavier Pennec, Adrian V. Dalca, Sarah Parisot, Sarang C. Joshi, Nematollah Kayhan Batmanghelich, Aristeidis Sotiras, Mads Nielsen, Mert R. Sabuncu, Tom Fletcher, Li Shen, Stanley Durrleman, Stefan Sommer:
Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - First International Workshop, GRAIL 2017, 6th International Workshop, MFCA 2017, and Third International Workshop, MICGen 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10-14, 2017, Proceedings. Lecture Notes in Computer Science 10551, Springer 2017, ISBN 978-3-319-67674-6 [contents] - [e5]M. Jorge Cardoso, Tal Arbel, Su-Lin Lee, Veronika Cheplygina, Simone Balocco, Diana Mateus, Guillaume Zahnd, Lena Maier-Hein, Stefanie Demirci, Eric Granger, Luc Duong, Marc-André Carbonneau, Shadi Albarqouni, Gustavo Carneiro:
Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis - 6th Joint International Workshops, CVII-STENT 2017 and Second International Workshop, LABELS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10-14, 2017, Proceedings. Lecture Notes in Computer Science 10552, Springer 2017, ISBN 978-3-319-67533-6 [contents] - [e4]M. Jorge Cardoso, Tal Arbel, Gustavo Carneiro, Tanveer F. Syeda-Mahmood, João Manuel R. S. Tavares, Mehdi Moradi, Andrew P. Bradley, Hayit Greenspan, João Paulo Papa, Anant Madabhushi, Jacinto C. Nascimento, Jaime S. Cardoso, Vasileios Belagiannis, Zhi Lu:
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support - Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, 2017, Proceedings. Lecture Notes in Computer Science 10553, Springer 2017, ISBN 978-3-319-67557-2 [contents] - [e3]M. Jorge Cardoso, Tal Arbel, Andrew Melbourne, Hrvoje Bogunovic, Pim Moeskops, Xinjian Chen, Ernst Schwartz, Mona Kathryn Garvin, Emma C. Robinson, Emanuele Trucco, Michael Ebner, Yanwu Xu, Antonios Makropoulos, Adrien E. Desjardins, Tom Vercauteren:
Fetal, Infant and Ophthalmic Medical Image Analysis - International Workshop, FIFI 2017, and 4th International Workshop, OMIA 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, 2017, Proceedings. Lecture Notes in Computer Science 10554, Springer 2017, ISBN 978-3-319-67560-2 [contents] - [e2]M. Jorge Cardoso, Tal Arbel, Fei Gao, Bernhard Kainz, Theo van Walsum, Kuangyu Shi, Kanwal K. Bhatia, Roman Peter, Tom Vercauteren, Mauricio Reyes, Adrian V. Dalca, Roland Wiest, Wiro J. Niessen, Bart J. Emmer:
Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment - Fifth International Workshop, CMMI 2017, Second International Workshop, RAMBO 2017, and First International Workshop, SWITCH 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, 2017, Proceedings. Lecture Notes in Computer Science 10555, Springer 2017, ISBN 978-3-319-67563-3 [contents] - [i1]Qing Tian, Tal Arbel, James J. Clark:
Efficient Gender Classification Using a Deep LDA-Pruned Net. CoRR abs/1704.06305 (2017) - 2016
- [j29]Tal Arbel, Manuel Jorge Cardoso, William M. Wells III, Albert C. S. Chung, Doina Precup:
Editorial on Special Issue on Probabilistic Models for Biomedical Image Analysis. Comput. Vis. Image Underst. 151: 1-2 (2016) - [j28]Zahra Karimaghaloo, Douglas L. Arnold, Tal Arbel:
Adaptive multi-level conditional random fields for detection and segmentation of small enhanced pathology in medical images. Medical Image Anal. 27: 17-30 (2016) - [j27]Rashed Karim, Pranav Bhagirath, Piet Claus, Richard James Housden, Zhong Chen, Zahra Karimaghaloo, Hyon-Mok Sohn, Laura Lara Rodríguez, Sergio Vera, Xènia Albà, Anja Hennemuth, Heinz-Otto Peitgen, Tal Arbel, Miguel Ángel González Ballester, Alejandro F. Frangi, Marco Götte, Reza Razavi, Tobias Schaeffter, Kawal S. Rhode:
Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late Gadolinium enhancement MR images. Medical Image Anal. 30: 95-107 (2016) - [j26]Meltem Demirkus, Doina Precup, James J. Clark, Tal Arbel:
Hierarchical Spatio-Temporal Probabilistic Graphical Model with Multiple Feature Fusion for Binary Facial Attribute Classification in Real-World Face Videos. IEEE Trans. Pattern Anal. Mach. Intell. 38(6): 1185-1203 (2016) - [c51]Qing Tian, Tal Arbel, James J. Clark:
Shannon information based adaptive sampling for action recognition. ICPR 2016: 967-972 - [c50]Ian J. Gerard, C. Couturier, Marta Kersten-Oertel, Simon Drouin, Dante De Nigris, Jeffery A. Hall, Kelvin Mok, Kevin Petrecca, Tal Arbel, D. Louis Collins:
Towards a Second Brain Images of Tumours for Evaluation (BITE2) Database. BrainLes@MICCAI 2016: 16-22 - 2015
- [j25]Meltem Demirkus, Doina Precup, James J. Clark, Tal Arbel:
Hierarchical temporal graphical model for head pose estimation and subsequent attribute classification in real-world videos. Comput. Vis. Image Underst. 136: 128-145 (2015) - [j24]Rola Harmouche, Nagesh K. Subbanna, D. Louis Collins, Douglas L. Arnold, Tal Arbel:
Probabilistic Multiple Sclerosis Lesion Classification Based on Modeling Regional Intensity Variability and Local Neighborhood Information. IEEE Trans. Biomed. Eng. 62(5): 1281-1292 (2015) - [j23]Zahra Karimaghaloo, Hassan Rivaz, Douglas L. Arnold, D. Louis Collins, Tal Arbel:
Temporal Hierarchical Adaptive Texture CRF for Automatic Detection of Gadolinium-Enhancing Multiple Sclerosis Lesions in Brain MRI. IEEE Trans. Medical Imaging 34(6): 1227-1241 (2015) - [j22]Bjoern H. Menze, András Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Keyvan Farahani, Justin S. Kirby, Yuliya Burren, Nicole Porz, Johannes Slotboom, Roland Wiest, Levente Lanczi, Elizabeth R. Gerstner, Marc-André Weber, Tal Arbel, Brian B. Avants, Nicholas Ayache, Patricia Buendia, D. Louis Collins, Nicolas Cordier, Jason J. Corso, Antonio Criminisi, Tilak Das, Herve Delingette, Çagatay Demiralp, Christopher R. Durst, Michel Dojat, Senan Doyle, Joana Festa, Florence Forbes, Ezequiel Geremia, Ben Glocker, Polina Golland, Xiaotao Guo, Andac Hamamci, Khan M. Iftekharuddin, Raj Jena, Nigel M. John, Ender Konukoglu, Danial Lashkari, José Antonio Mariz, Raphael Meier, Sérgio Pereira, Doina Precup, Stephen J. Price, Tammy Riklin Raviv, Syed M. S. Reza, Michael T. Ryan, Duygu Sarikaya, Lawrence H. Schwartz, Hoo-Chang Shin, Jamie Shotton, Carlos A. Silva, Nuno J. Sousa, Nagesh K. Subbanna, Gábor Székely, Thomas J. Taylor, Owen M. Thomas, Nicholas J. Tustison, Gözde B. Ünal, Flor Vasseur, Max Wintermark, Dong Hye Ye, Liang Zhao, Binsheng Zhao, Darko Zikic, Marcel Prastawa, Mauricio Reyes, Koen Van Leemput:
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS). IEEE Trans. Medical Imaging 34(10): 1993-2024 (2015) - [c49]Nagesh K. Subbanna, Doina Precup, Douglas L. Arnold, Tal Arbel:
IMaGe: Iterative Multilevel Probabilistic Graphical Model for Detection and Segmentation of Multiple Sclerosis Lesions in Brain MRI. IPMI 2015: 514-526 - [c48]