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Kuijf, Hugo J; Biesbroek, J Matthijs; de Bresser, Jeroen; Heinen, Rutger; Andermatt, Simon; Bento, Mariana; Berseth, Matt; Belyaev, Mikhail; Cardoso, M Jorge; Casamitjana, Adria; Collins, D Louis; Dadar, Mahsa; Georgiou, Achilleas; Ghafoorian, Mohsen; Jin, Dakai; Khademi, April; Knight, Jesse; Li, Hongwei; Llado, Xavier; Luna, Miguel; ... (2019). Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities; Results of the WMH Segmentation Challenge. IEEE transactions on medical imaging, 38(11), pp. 2556-2568. Institute of Electrical and Electronics Engineers IEEE 10.1109/TMI.2019.2905770
McKinley, Richard; Marshall, Randolph (2019). Advanced MRI in acute stroke: Is the whole penumbra salvageable? Neurology, 92(21), pp. 983-984. American Academy of Neurology 10.1212/WNL.0000000000007535
Rebsamen, Michael; Knecht, Urspeter; Reyes, Mauricio; Wiest, Roland; Meier, Raphael; McKinley, Richard (2019). Divide and Conquer: Stratifying Training Data by Tumor Grade Improves Deep Learning-Based Brain Tumor Segmentation. Frontiers in neuroscience, 13, p. 1182. Frontiers Research Foundation 10.3389/fnins.2019.01182
Commowick, Olivier; Istace, Audrey; Kain, Michaël; Laurent, Baptiste; Leray, Florent; Simon, Mathieu; Pop, Sorina Camarasu; Girard, Pascal; Améli, Roxana; Ferré, Jean-Christophe; Kerbrat, Anne; Tourdias, Thomas; Cervenansky, Frédéric; Glatard, Tristan; Beaumont, Jérémy; Doyle, Senan; Forbes, Florence; Knight, Jesse; Khademi, April; Mahbod, Amirreza; ... (2018). Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure. Scientific Reports, 8(1), p. 13650. Nature Publishing Group 10.1038/s41598-018-31911-7
Pereira, Sérgio; Meier, Raphael; McKinley, Richard; Wiest, Roland; Alves, Victor; Silva, Carlos A; Reyes, Mauricio (2018). Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation. Medical image analysis, 44, pp. 228-244. Elsevier 10.1016/j.media.2017.12.009
Rummel, Christian; Aschwanden, Fabian; McKinley, Richard; Wagner, Franca; Salmen, Anke; Chan, Andrew; Wiest, Roland (2018). A Fully Automated Pipeline for Normative Atrophy in Patients with Neurodegenerative Disease. Frontiers in neurology, 8, p. 727. Frontiers Media S.A. 10.3389/fneur.2017.00727
McKinley, Richard; Hung, Fan; Wiest, Roland; Liebeskind, David S; Scalzo, Fabien (2018). A Machine Learning Approach to Perfusion Imaging With Dynamic Susceptibility Contrast MR. Frontiers in neurology, 9(717), p. 717. Frontiers Media S.A. 10.3389/fneur.2018.00717
Winzeck, Stefan; Hakim, Arsany; McKinley, Richard; Pinto, José A A D S R; Alves, Victor; Silva, Carlos; Pisov, Maxim; Krivov, Egor; Belyaev, Mikhail; Monteiro, Miguel; Oliveira, Arlindo; Choi, Youngwon; Paik, Myunghee Cho; Kwon, Yongchan; Lee, Hanbyul; Kim, Beom Joon; Won, Joong-Ho; Islam, Mobarakol; Ren, Hongliang; Robben, David; ... (2018). ISLES 2016 and 2017-Benchmarking Ischemic Stroke Lesion Outcome Prediction Based on Multispectral MRI. Frontiers in neurology, 9(679), p. 679. Frontiers Media S.A. 10.3389/fneur.2018.00679
Pinto, Adriano; McKinley, Richard; Alves, Victor; Wiest, Roland; Silva, Carlos A; Reyes, Mauricio (2018). Stroke Lesion Outcome Prediction Based on MRI Imaging Combined With Clinical Information. Frontiers in neurology, 9(1060), p. 1060. Frontiers Media S.A. 10.3389/fneur.2018.01060
Habegger, Simon; Wiest, Roland; Weder, Bruno; Mordasini, Pasquale; Gralla, Jan; Häni, Levin; Jung, Simon; Reyes, Mauricio; McKinley, Richard (2018). Relating Acute Lesion Loads to Chronic Outcome in Ischemic Stroke-An Exploratory Comparison of Mismatch Patterns and Predictive Modeling. Frontiers in neurology, 9(737), p. 737. Frontiers Media S.A. 10.3389/fneur.2018.00737
Jung, Simon; Wiest, Roland; Gralla, Jan; McKinley, Richard; Mattle, Heinrich; Liebeskind, David (2017). Relevance of the cerebral collateral circulation in ischaemic stroke: time is brain, but collaterals set the pace. Swiss medical weekly, 147(w14538), w14538. EMH Schweizerischer Ärzteverlag 10.4414/smw.2017.14538
Da Silva Mendes Pedrosa, Nuno Miguel; McKinley, Richard; Wiest, Roland; Slotboom, Johannes (2017). Improving labeling efficiency in automatic quality control of MRSI data. Magnetic resonance in medicine, 78(6), pp. 2399-2405. Wiley-Liss 10.1002/mrm.26618
Maier, Oskar; Menze, Bjoern H; von der Gablentz, Janina; Häni, Levin; Heinrich, Mattias P; Liebrand, Matthias; Winzeck, Stefan; Basit, Abdul; Bentley, Paul; Chen, Liang; Christiaens, Daan; Dutil, Francis; Egger, Karl; Feng, Chaolu; Glocker, Ben; Götz, Michael; Haeck, Tom; Halme, Hanna-Leena; Havaei, Mohammad; Iftekharuddin, Khan M; ... (2016). ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI. Medical image analysis, 35, pp. 250-269. Elsevier 10.1016/j.media.2016.07.009
Da Silva Mendes Pedrosa, Nuno Miguel; McKinley, Richard; Knecht, Urspeter; Wiest, Roland; Slotboom, Johannes (2016). Automatic quality control in clinical (1) H MRSI of brain cancer. NMR in biomedicine, 29(5), pp. 563-575. Wiley Interscience 10.1002/nbm.3470
McKinley, Richard; Häni, Levin; Gralla, Jan; El-Koussy, Marwan; Bauer, S; Arnold, Marcel; Fischer, Urs; Jung, Simon; Mattmann, Kaspar; Reyes, Mauricio; Wiest, Roland (2016). Fully automated stroke tissue estimation using random forest classifiers (FASTER). Journal of cerebral blood flow and metabolism, 37(8), pp. 2728-2741. Nature Publishing Group 10.1177/0271678X16674221
McKinley, Richard (2013). Canonical proof nets for classical logic. Annals of pure and applied logic, 164(6), pp. 702-732. Elsevier 10.1016/j.apal.2012.05.007
McKinley, Richard (2013). Proof Nets for Herbrand’s Theorem. ACM transactions on computational logic, 14(1), pp. 1-31. New York: ACM 10.1145/2422085.2422090
McKinley, Richard (2008). Soft linear set theory. Journal of logic and algebraic programming, 76(2), pp. 226-245. New York, N.Y.: North-Holland 10.1016/j.jlap.2008.02.010
Rebsamen, Michael; Rummel, Christian; Mürner-Lavanchy, Ines; Reyes, M; Wiest, Roland; McKinley, Richard (2019). Surface-Based Brain Morphometry for the Prediction of Fluid Intelligence in the Neurocognitive Prediction Challenge 2019. In: Pohl, Kilian M.; Thompson, Wesley K.; Adeli, Ehsan; Linguraru, Marius George (eds.) Adolescent Brain Cognitive Development Neurocognitive Prediction. ABCD-NP 2019. Lecture notes in computer science: Vol. 11791 (pp. 26-34). Cham, Switzerland: Springer
McKinley, Richard (2010). Expansion nets: Proof nets for propositional classical logic. In: Fermüller, Christian; Voronkov, Andrei (eds.) Logic for Programming, Artificial Intelligence, and Reasoning. 17th International Conference, LPAR-17, Yogyakarta, Indonesia, October 10-15, 2010. Proceedings 6397 (pp. 535-549). Heidelberg: Springer Verlag 10.1007/978-3-642-16242-8
Brünnler, Kai; McKinley, Richard (2008). An Algorithmic Interpretation of a Deep Inference System. In: Cervesato, Iliano; Veith, Helmut; Voronkov, Andrei (eds.) Logic for Programming, Artificial Intelligence, and Reasoning. 15th International Conference, LPAR 2008, Doha, Qatar, November 22-27, 2008. Proceedings. Lecture Notes in Computer Science: Vol. 5330 (pp. 482-496). Heidelberg: Springer Verlag 10.1007/978-3-540-89439-1_34
McKinley, Richard (2009). The alpha-epsilon calculus. In: Proceedings of Workshop on Structures and Deduction.
