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Deep Learning Versus Classical Regression for Brain Tumor Patient Survival Prediction.

, , , , , , и . BrainLes@MICCAI (2), том 11384 из Lecture Notes in Computer Science, стр. 429-440. Springer, (2018)

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Deep Learning Versus Classical Regression for Brain Tumor Patient Survival Prediction., , , , , , и . BrainLes@MICCAI (2), том 11384 из Lecture Notes in Computer Science, стр. 429-440. Springer, (2018)Spatially regularized parametric map reconstruction for fast magnetic resonance fingerprinting., , , , , и . Medical Image Anal., (2020)Unsupervised out-of-distribution detection for safer robotically guided retinal microsurgery., , , , , , и . Int. J. Comput. Assist. Radiol. Surg., 18 (6): 1085-1091 (2023)The MICCAI Hackathon on reproducibility, diversity, and selection of papers at the MICCAI conference., , , , , , , , , и 5 other автор(ы). CoRR, (2021)Uncertainty-driven Sanity Check: Application to Postoperative Brain Tumor Cavity Segmentation., , , , и . CoRR, (2018)Spatially Regularized Parametric Map Reconstruction for Fast Magnetic Resonance Fingerprinting., , , , , и . CoRR, (2019)Assessing Reliability and Challenges of Uncertainty Estimations for Medical Image Segmentation., и . MICCAI (2), том 11765 из Lecture Notes in Computer Science, стр. 48-56. Springer, (2019)pymia: A Python package for data handling and evaluation in deep learning-based medical image analysis., , , и . CoRR, (2020)Perturb-and-MPM: Quantifying Segmentation Uncertainty in Dense Multi-Label CRFs., , , , и . CoRR, (2017)On the Effect of Inter-observer Variability for a Reliable Estimation of Uncertainty of Medical Image Segmentation., , , , , , и . MICCAI (1), том 11070 из Lecture Notes in Computer Science, стр. 682-690. Springer, (2018)