Richard McKinley
Orcid: 0000-0001-8250-6117
According to our database1,
Richard McKinley
authored at least 25 papers
between 2008 and 2023.
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Bibliography
2023
CortexMorph: Fast Cortical Thickness Estimation via Diffeomorphic Registration Using VoxelMorph.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Federated Learning on Heterogeneous Diffusion-Weighted Imaging Data for Acute Stroke Infarct Segmentation.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
2022
Weighting Schemes for Federated Learning in Heterogeneous and Imbalanced Segmentation Datasets.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2022
2021
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results.
CoRR, 2021
Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient.
CoRR, 2021
2020
Uncertainty-Driven Refinement of Tumor-Core Segmentation Using 3D-to-2D Networks with Label Uncertainty.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020
2019
Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge.
IEEE Trans. Medical Imaging, 2019
Automatic detection of lesion load change in Multiple Sclerosis using convolutional neural networks with segmentation confidence.
CoRR, 2019
Few-shot brain segmentation from weakly labeled data with deep heteroscedastic multi-task networks.
CoRR, 2019
Simultaneous lesion and neuroanatomy segmentation in Multiple Sclerosis using deep neural networks.
CoRR, 2019
Surface-Based Brain Morphometry for the Prediction of Fluid Intelligence in the Neurocognitive Prediction Challenge 2019.
Proceedings of the Adolescent Brain Cognitive Development Neurocognitive Prediction, 2019
Triplanar Ensemble of 3D-to-2D CNNs with Label-Uncertainty for Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019
2018
Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation.
Medical Image Anal., 2018
Ensembles of Densely-Connected CNNs with Label-Uncertainty for Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018
2017
Pooling-Free Fully Convolutional Networks with Dense Skip Connections for Semantic Segmentation, with Application to Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017
2016
Nabla-net: A Deep Dag-Like Convolutional Architecture for Biomedical Image Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2016
2015
Segmenting the Ischemic Penumbra: A Decision Forest Approach with Automatic Threshold Finding.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2015
2013
2010
Proceedings of the Logic for Programming, Artificial Intelligence, and Reasoning, 2010
2008
Proceedings of the Logic for Programming, 2008