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ORCIDRichard McKinley
- > Home > Persons > Richard McKinley
Publications
- 2025
[e1]Ruisheng Su
, Ezequiel de la Rosa, Leonhard Rist, Ewout Heylen, Frank te Nijenhuis, Danny Ruijters, Markus D. Schirmer, Richard McKinley, Susanne Wegener, Roland Wiest, Theo van Walsum:
Image Analysis in Stroke Diagnosis and Interventions - 4th International Workshop, SWITCH 2024, and 6th International Challenge, ISLES 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings. Lecture Notes in Computer Science 15408, Springer 2025, ISBN 978-3-031-81100-5 [contents]- [i15]Ivan Diaz, Florin Scherer, Yanik Berli, Roland Wiest, Helly N. Hammer, Robert Hoepner, Alejandro Leon Betancourt, Piotr Radojewski, Richard McKinley:
Learning from spatially inhomogenous data: resolution-adaptive convolutions for multiple sclerosis lesion segmentation. CoRR abs/2503.21829 (2025) - 2023
- [c15]Theo Leuliet, Stefan Huwer, Bénédicte Maréchal, Veronica Ravano, Tobias Kober, Jonathan Rafael-Patino, Johannes Kaesmacher, Roland Wiest, Jonas Richiardi, Richard McKinley:
Deep Learning for Ischemic Penumbra Segmentation from MR Perfusion Maps: Robustness to the Deconvolution Algorithm. BrainLes/SWITCH@MICCAI 2023: 106-114 - [c14]Antoine Madrona, Sebastian Otálora, Elda Fischi Gomez, Veronica Ravano, Bénédicte Maréchal, Jean-Philippe Thiran, Tobias Kober, Roland Wiest, Richard McKinley, Jonas Richiardi, Jonathan Rafael-Patino:
Federated Learning on Heterogeneous Diffusion-Weighted Imaging Data for Acute Stroke Infarct Segmentation. ISBI 2023: 1-5 - 2022
- [c12]Sebastian Otálora, Jonathan Rafael-Patino, Antoine Madrona, Elda Fischi Gomez, Veronica Ravano, Tobias Kober, Søren Christensen, Arsany Hakim, Roland Wiest, Jonas Richiardi, Richard McKinley:
Weighting Schemes for Federated Learning in Heterogeneous and Imbalanced Segmentation Datasets. BrainLes@MICCAI 2022: 45-56 - 2021
- [i10]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
- [c11]Richard McKinley, Michael Rebsamen, Katrin Daetwyler, Raphael Meier, Piotr Radojewski, Roland Wiest:
Uncertainty-Driven Refinement of Tumor-Core Segmentation Using 3D-to-2D Networks with Label Uncertainty. BrainLes@MICCAI (1) 2020: 401-411 - [i9]Richard McKinley, Michael Rebsamen, Katrin Daetwyler, Raphael Meier, Piotr Radojewski, Roland Wiest:
Uncertainty-driven refinement of tumor-core segmentation using 3D-to-2D networks with label uncertainty. CoRR abs/2012.06436 (2020) - 2019
- [j5]Hugo J. Kuijf, Adrià Casamitjana, D. Louis Collins, Mahsa Dadar, Achilleas Georgiou, Mohsen Ghafoorian, Dakai Jin, April Khademi, Jesse Knight, Hongwei Li, Xavier Lladó, J. Matthijs Biesbroek, Miguel Luna, Qaiser Mahmood, Richard McKinley, Alireza Mehrtash, Sébastien Ourselin, Bo-yong Park, Hyunjin Park, Sang Hyun Park, Simon Pezold, Élodie Puybareau, Jeroen de Bresser, Letícia Rittner, Carole H. Sudre, Sergi Valverde, Verónica Vilaplana, Roland Wiest, Yongchao Xu, Ziyue Xu, Guodong Zeng, Jianguo Zhang, Guoyan Zheng, Rutger Heinen, Christopher Li Hsian Chen, Wiesje M. van der Flier, Frederik Barkhof, Max A. Viergever, Geert Jan Biessels, Simon Andermatt, Mariana P. Bento, Matt Berseth, Mikhail Belyaev, M. Jorge Cardoso:
Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge. IEEE Trans. Medical Imaging 38(11): 2556-2568 (2019) - [c10]Richard McKinley, Michael Rebsamen, Raphael Meier, Roland Wiest:
Triplanar Ensemble of 3D-to-2D CNNs with Label-Uncertainty for Brain Tumor Segmentation. BrainLes@MICCAI (1) 2019: 379-387 - [c9]Michael Rebsamen, Christian Rummel, Ines Mürner-Lavanchy, Mauricio Reyes, Roland Wiest, Richard McKinley:
Surface-Based Brain Morphometry for the Prediction of Fluid Intelligence in the Neurocognitive Prediction Challenge 2019. ABCD-NP@MICCAI 2019: 26-34 - [i8]Richard McKinley, Rik Wepfer, Fabian Aschwanden, Lorenz Grunder, Raphaela Muri, Christian Rummel, Rajeev Verma, Christian Weisstanner, Mauricio Reyes, Anke Salmen, Andrew Chan, Franca Wagner, Roland Wiest:
Simultaneous lesion and neuroanatomy segmentation in Multiple Sclerosis using deep neural networks. CoRR abs/1901.07419 (2019) - [i7]Hugo J. Kuijf, J. Matthijs Biesbroek, Jeroen de Bresser, Rutger Heinen, Simon Andermatt, Mariana P. Bento, Matt Berseth, Mikhail Belyaev, M. Jorge Cardoso, Adrià Casamitjana, D. Louis Collins, Mahsa Dadar, Achilleas Georgiou, Mohsen Ghafoorian, Dakai Jin, April Khademi, Jesse Knight, Hongwei Li, Xavier Lladó, Miguel Luna, Qaiser Mahmood, Richard McKinley, Alireza Mehrtash, Sébastien Ourselin, Bo-yong Park, Hyunjin Park, Sang Hyun Park, Simon Pezold, Élodie Puybareau, Letícia Rittner, Carole H. Sudre, Sergi Valverde, Verónica Vilaplana, Roland Wiest, Yongchao Xu, Ziyue Xu, Guodong Zeng, Jianguo Zhang, Guoyan Zheng, Christopher Li Hsian Chen, Wiesje M. van der Flier, Frederik Barkhof, Max A. Viergever, Geert Jan Biessels:
Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge. CoRR abs/1904.00682 (2019) - [i6]Richard McKinley, Michael Rebsamen, Raphael Meier, Mauricio Reyes, Christian Rummel, Roland Wiest:
Few-shot brain segmentation from weakly labeled data with deep heteroscedastic multi-task networks. CoRR abs/1904.02436 (2019) - [i5]Richard McKinley, Lorenz Grunder, Rik Wepfer, Fabian Aschwanden, Tim Fischer, Christoph Friedli, Raphaela Muri, Christian Rummel, Rajeev Verma, Christian Weisstanner, Mauricio Reyes, Anke Salmen, Andrew Chan, Roland Wiest, Franca Wagner:
Automatic detection of lesion load change in Multiple Sclerosis using convolutional neural networks with segmentation confidence. CoRR abs/1904.03041 (2019) - 2018
- [j4]Sérgio Pereira, Raphael Meier, Richard McKinley, Roland Wiest, Victor Alves, Carlos A. Silva, Mauricio Reyes:
Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation. Medical Image Anal. 44: 228-244 (2018) - [c8]Andreas Hess, Raphael Meier, Johannes Kaesmacher, Simon Jung, Fabien Scalzo, David S. Liebeskind, Roland Wiest, Richard McKinley:
Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learning. BrainLes@MICCAI (1) 2018: 447-455 - [c7]Richard McKinley, Raphael Meier, Roland Wiest:
Ensembles of Densely-Connected CNNs with Label-Uncertainty for Brain Tumor Segmentation. BrainLes@MICCAI (2) 2018: 456-465 - [i3]Andreas Hess, Raphael Meier, Johannes Kaesmacher, Simon Jung, Fabien Scalzo, David S. Liebeskind, Roland Wiest, Richard McKinley:
Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learning. CoRR abs/1806.03848 (2018) - 2017
- [c6]Richard McKinley, Alain Jungo, Roland Wiest, Mauricio Reyes:
Pooling-Free Fully Convolutional Networks with Dense Skip Connections for Semantic Segmentation, with Application to Brain Tumor Segmentation. BrainLes@MICCAI 2017: 169-177 - [c5]Alain Jungo, Richard McKinley, Raphael Meier, Urspeter Knecht, Luis Vera, Julián Pérez-Beteta, David Molina-García, Víctor M. Pérez-García, Roland Wiest, Mauricio Reyes:
Towards Uncertainty-Assisted Brain Tumor Segmentation and Survival Prediction. BrainLes@MICCAI 2017: 474-485 - 2016
- [c4]Richard McKinley, Rik Wepfer, Tom Gundersen, Franca Wagner, Andrew Chan, Roland Wiest, Mauricio Reyes:
Nabla-net: A Deep Dag-Like Convolutional Architecture for Biomedical Image Segmentation. BrainLes@MICCAI 2016: 119-128 - 2015
- [c3]Richard McKinley, Levin Häni, Roland Wiest, Mauricio Reyes:
Segmenting the Ischemic Penumbra: A Decision Forest Approach with Automatic Threshold Finding. Brainles@MICCAI 2015: 275-283
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