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Deep learning for brain tumor classification., , , и . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, том 10137 из SPIE Proceedings, стр. 1013710. SPIE, (2017)Revealing latent value of clinically acquired CTs of traumatic brain injury through multi-atlas segmentation in a retrospective study of 1, 003 with external cross-validation., , , , , и . Medical Imaging: Image Processing, том 9413 из SPIE Proceedings, стр. 94130K. SPIE, (2015)Technology Enablers for Big Data, Multi-Stage Analysis in Medical Image Processing., , , , , , , , , и 1 other автор(ы). IEEE BigData, стр. 1337-1346. IEEE, (2018)Sequence-Aware and Advanced Biomarker Calculation Improves Statistical Inference in Image Processing of Parkinson's Disease.. Vanderbilt University, Nashville, Tennessee, USA, (2017)base-search.net (ftvanderbilt:oai:ir.vanderbilt.edu:1803/14512).Multi-atlas learner fusion: An efficient segmentation approach for large-scale data., , , и . Medical Image Anal., 26 (1): 82-91 (2015)A Data Colocation Grid Framework for Big Data Medical Image Processing - Backend Design., , , , , , , , и . CoRR, (2017)Multi-scale hippocampal parcellation improves atlas-based segmentation accuracy., , , и . Medical Imaging: Image Processing, том 10133 из SPIE Proceedings, стр. 101332D. SPIE, (2017)On the fallacy of quantitative segmentation for T1-weighted MRI., , , , , , , , и . Medical Imaging: Image Processing, том 9784 из SPIE Proceedings, стр. 978416. SPIE, (2016)Structural-functional relationships between eye orbital imaging biomarkers and clinical visual assessments., , , , , , , и . Medical Imaging: Image Processing, том 10133 из SPIE Proceedings, стр. 101331F. SPIE, (2017)Toward content-based image retrieval with deep convolutional neural networks., , , и . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, том 9417 из SPIE Proceedings, стр. 94172C. SPIE, (2015)