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Quantifying image structures in high-throughput microscopy with total variation flow.

, , , , and . ISBI, page 381-385. IEEE, (2016)

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Fast, Accurate and Steerable Segmentation of Drusen in Optical Coherence Tomography. University of Bonn, Germany, (2020)base-search.net (ftunivbonn:oai:bonndoc.ulb.uni-bonn.de:20.500.11811/8642).Uncertainty-Guided Semi-Automated Editing of CNN-based Retinal Layer Segmentations in Optical Coherence Tomography., , and . VCBM@MICCAI, page 107-115. Eurographics Association, (2018)Bias in Cross-Entropy-Based Training of Deep Survival Networks., and . IEEE Trans. Pattern Anal. Mach. Intell., 43 (9): 3126-3137 (2021)CNNs Enable Accurate and Fast Segmentation of Drusen in Optical Coherence Tomography., , , , , , and . DLMIA/ML-CDS@MICCAI, volume 10553 of Lecture Notes in Computer Science, page 65-73. Springer, (2017)Quantifying image structures in high-throughput microscopy with total variation flow., , , , and . ISBI, page 381-385. IEEE, (2016)Multi-scale Anisotropic Fourth-Order Diffusion Improves Ridge and Valley Localization., , , and . Journal of Mathematical Imaging and Vision, 59 (2): 257-269 (2017)