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On Orthogonal Projections for Dimension Reduction and Applications in Augmented Target Loss Functions for Learning Problems.

, , , , , , , , и . J. Math. Imaging Vis., 62 (3): 376-394 (2020)

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Bianca Gerendas

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Motion Artefact Correction in Retinal Optical Coherence Tomography Using Local Symmetry., , , , , , и . MICCAI (2), том 8674 из Lecture Notes in Computer Science, стр. 130-137. Springer, (2014)Correction to: On Orthogonal Projections for Dimension Reduction and Applications in Augmented Target Loss Functions for Learning Problems., , , , , , , , и . J. Math. Imaging Vis., 62 (3): 395 (2020)Blood vessel segmentation in en-face OCTA images: a frequency based method., , , , и . Medical Imaging: Computer-Aided Diagnosis, том 12033 из SPIE Proceedings, SPIE, (2022)Spatio-Temporal Signatures to Predict Retinal Disease Recurrence., , , , , , , и . IPMI, том 9123 из Lecture Notes in Computer Science, стр. 152-163. Springer, (2015)Robust Fovea Detection in Retinal OCT Imaging Using Deep Learning., , , , и . IEEE J. Biomed. Health Informatics, 26 (8): 3927-3937 (2022)Unsupervised Identification of Disease Marker Candidates in Retinal OCT Imaging Data., , , , , , , , и . CoRR, (2018)U2-Net: A Bayesian U-Net Model With Epistemic Uncertainty Feedback For Photoreceptor Layer Segmentation In Pathological OCT Scans., , , , , , , и . ISBI, стр. 1441-1445. IEEE, (2019)A novel benchmark model for intelligent annotation of spectral-domain optical coherence tomography scans using the example of cyst annotation., , , , , , , , , и . Comput. Methods Programs Biomed., (2016)Improve synthetic retinal OCT images with present of pathologies and textural information., , , , , , , и . Medical Imaging: Image Processing, том 9784 из SPIE Proceedings, стр. 97843V. SPIE, (2016)On orthogonal projections for dimension reduction and applications in variational loss functions for learning problems., , , , , , , , и . CoRR, (2019)