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Eva Höck
Eva Höck
Carl Zeiss, Corporate Research & Technology
Verified email at zeiss.com
Title
Cited by
Cited by
Year
N2v2-fixing noise2void checkerboard artifacts with modified sampling strategies and a tweaked network architecture
E Höck, TO Buchholz, A Brachmann, F Jug, A Freytag
European Conference on Computer Vision, 503-518, 2022
52022
Live 4D-OCT denoising with self-supervised deep learning
J Nienhaus, P Matten, A Britten, J Scherer, E Höck, A Freytag, W Drexler, ...
Scientific Reports 13 (1), 5760, 2023
42023
Quantitative analysis before and after self-supervised denoising on OCTA images
Q Zhang, E Hoeck, M Shen, G Gregori, PJ Rosenfeld, N Manivannan
Investigative Ophthalmology & Visual Science 64 (9), PB0071-PB0071, 2023
2023
Self-supervised denoising using optimized blind-spot networks for real-time application in 4D-OCT
J Nienhaus, P Matten, A Britten, T Schlegl, E Höck, A Freytag, M Everett, ...
Medical Imaging 2023: Image Processing 12464, 424-428, 2023
2023
Real-time neural-network-based denoising for intraoperative 4D-OCT
J Nienhaus, P Matten, A Britten, T Schlegl, E Höck, A Freytag, M Everett, ...
Optical Coherence Tomography and Coherence Domain Optical Methods in …, 2023
2023
Improving OCT B-Scan classification feature attribution maps with adversarial training
N Spier, G Ghazaei, A Urich, E Hoeck, GC Lee, N Manivannan
Investigative Ophthalmology & Visual Science 62 (8), 2104-2104, 2021
2021
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