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Disambiguation of "Veta, Mitko"

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Domain-Adversarial Neural Networks to Address the Appearance Variability of Histopathology Images.

, , , , and . DLMIA/ML-CDS@MICCAI, volume 10553 of Lecture Notes in Computer Science, page 83-91. Springer, (2017)

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Mirjana Mitkov

Mitko Wassilew

Bernhard Mitko

Ruslan Mitkov

Teodora Mitkova

 

Other publications of authors with the same name

Capturing Single-Cell Phenotypic Variation via Unsupervised Representation Learning., , , , , and . MIDL, volume 102 of Proceedings of Machine Learning Research, page 315-325. PMLR, (2019)Quantifying Graft Detachment after Descemet's Membrane Endothelial Keratoplasty with Deep Convolutional Neural Networks., , , , and . CoRR, (2020)Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge., , , , , , , , , and 9 other author(s). Medical Image Anal., (2019)Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors., , , , , , , , , and 2 other author(s). CoRR, (2020)A Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging., , , , , , , , , and 34 other author(s). CoRR, (2020)Intensity Augmentation to Improve Generalizability of Breast Segmentation Across Different MRI Scan Protocols., , , and . IEEE Trans. Biomed. Eng., 68 (3): 759-770 (2021)LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset., , , , , , , , , and 11 other author(s). IEEE J. Biomed. Health Informatics, 28 (3): 1161-1172 (March 2024)Inferring a third spatial dimension from 2D histological images., , , , and . ISBI, page 586-589. IEEE, (2018)Optimized automated cardiac MR scar quantification with GAN-based data augmentation., , , , and . Comput. Methods Programs Biomed., (2022)Detection of acini in histopathology slides: towards automated prediction of breast cancer risk., , , , , , , and . Medical Imaging: Digital Pathology, volume 10956 of SPIE Proceedings, page 109560Q. SPIE, (2019)