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Reliability of using single specialist annotation for designing and evaluating automatic segmentation methods: A skull stripping case study.

, , , , , , , and . ISBI, page 1344-1347. IEEE, (2018)

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Deep Learning in Large and Multi-Site Structural Brain MR Imaging Datasets., , , , and . Frontiers Neuroinformatics, (2021)V-Net and U-Net for Ischemic Stroke Lesion Segmentation in a Small Dataset of Perfusion Data., , , and . BrainLes@MICCAI (1), volume 11383 of Lecture Notes in Computer Science, page 301-309. Springer, (2018)Adessowiki: Collaborative Scientific Programming Environment., , , , , and . SIBGRAPI Tutorials, page 56-62. IEEE Computer Society, (2011)Normal Brain Aging: Prediction of Age, Sex and White Matter Hyperintensities Using a MR Image-Based Machine Learning Technique., , , and . ICIAR, volume 10882 of Lecture Notes in Computer Science, page 538-545. Springer, (2018)Dual-domain Cascade of U-nets for Multi-channel Magnetic Resonance Image Reconstruction., , , , , and . CoRR, (2019)Data-Driven Corpus Callosum Parcellation Method Through Diffusion Tensor Imaging., , , , and . IEEE Access, (2017)A voxel-level approach to brain age prediction: A method to assess regional brain aging., , , , , , and . CoRR, (2023)Reframing the Brain Age Prediction Problem to a More Interpretable and Quantitative Approach., , , , and . CoRR, (2023)Reliability of using single specialist annotation for designing and evaluating automatic segmentation methods: A skull stripping case study., , , , , , , and . ISBI, page 1344-1347. IEEE, (2018)Automated quality check of corpus callosum segmentation using deep learning., , , , , and . Medical Imaging: Image Processing, volume 12032 of SPIE Proceedings, SPIE, (2022)