Richard McKinley

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 25

Top Topics

Diffeomorphic Registration

Brain Tumor Segmentation

Weakly Labeled Data

Top Venues

BrainLes@MICCAI

BrainLes@MICCAI (1)

Brainles@MICCAI

Publications

Stefano Moriconi, Omar Rodríguez-Núñez, Romain Gros, Leonard A. Felger, Theoni Maragkou, Ekkehard Hewer, Angelo Pierangelo, Tatiana Novikova, Philippe Schucht, Richard McKinley
Near-real-time Mueller polarimetric image processing for neurosurgical intervention. Int. J. Comput. Assist. Radiol. Surg. 19 (6) (2024)
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)
Richard McKinley, Christian Rummel
CortexMorph: Fast Cortical Thickness Estimation via Diffeomorphic Registration Using VoxelMorph. MICCAI (10) (2023)
Richard McKinley, Christian Rummel
CortexMorph: fast cortical thickness estimation via diffeomorphic registration using VoxelMorph. CoRR (2023)
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)
Florian Kofler, Ivan Ezhov, Fabian Isensee, Fabian Balsiger, Christoph Berger, Maximilian Koerner, Johannes C. Paetzold, Hongwei Li, Suprosanna Shit, Richard McKinley, Spyridon Bakas, Claus Zimmer, Donna P. Ankerst, Jan Kirschke, Benedikt Wiestler, Bjoern H. Menze
Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient. CoRR (2021)
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, 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 Meyer, Nisarg A. Shah, Sanjay 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 (2021)
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)
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 (2020)
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 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 (2019)
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 (2019)
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 (2019)
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)
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 (2019)
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)
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 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) (2019)
Ahmed Hosny, Michael Schwier, Christoph Berger, Evin Pinar Örnek, Mehmet Turan, Phi V. Tran, Leon Weninger, Fabian Isensee, Klaus H. Maier-Hein, Richard McKinley, Michael T. Lu, Udo Hoffmann, Bjoern H. Menze, Spyridon Bakas, Andriy Fedorov, Hugo J. W. L. Aerts
ModelHub.AI: Dissemination Platform for Deep Learning Models. CoRR (2019)
Richard McKinley, Raphael Meier, Roland Wiest
Ensembles of Densely-Connected CNNs with Label-Uncertainty for Brain Tumor Segmentation. BrainLes@MICCAI (2) (2018)
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 (2018)
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)
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 (2018)
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)
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)
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)
Richard McKinley, Levin Häni, Roland Wiest, Mauricio Reyes
Segmenting the Ischemic Penumbra: A Decision Forest Approach with Automatic Threshold Finding. Brainles@MICCAI (2015)
Richard McKinley
Canonical proof nets for classical logic. Ann. Pure Appl. Log. 164 (6) (2013)
Richard McKinley
Proof Nets for Herbrand's Theorem. ACM Trans. Comput. Log. 14 (1) (2013)
Richard McKinley
Canonical Proof nets for Classical Logic CoRR (2012)
Richard McKinley
Proof nets for Herbrand's Theorem CoRR (2010)
Richard McKinley
Expansion Nets: Proof-Nets for Propositional Classical Logic. LPAR (Yogyakarta) (2010)
Richard McKinley
Soft Linear Set Theory. J. Log. Algebraic Methods Program. 76 (2) (2008)
Kai Brünnler, Richard McKinley
An Algorithmic Interpretation of a Deep Inference System. LPAR (2008)