Deep learning based hybrid OCT-OCTA segmentation of Bruch's membrane in pathology

Schottenhamml J, Ploner S, Moult EM, Duker JS, Waheed NK, Fujimoto JG, Maier A (2019)

Publication Type: Conference contribution

Publication year: 2019

Journal

Investigative Ophthalmology & Visual Science Association for Research in Vision and Ophthalmology (ARVO)

Publisher: ASSOC RESEARCH VISION OPHTHALMOLOGY INC

City/Town: ROCKVILLE

Conference Proceedings Title: INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE

Event location: Vancouver CA

Authors with CRIS profile

Julia Schottenhamml Lehrstuhl für Informatik 5 (Mustererkennung) Stefan Ploner Lehrstuhl für Informatik 5 (Mustererkennung) Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung)

Involved external institutions

Tufts University US United States (USA) (US) Massachusetts Institute of Technology (MIT) US United States (USA) (US)

How to cite

APA:

Schottenhamml, J., Ploner, S., Moult, E.M., Duker, J.S., Waheed, N.K., Fujimoto, J.G., & Maier, A. (2019). Deep learning based hybrid OCT-OCTA segmentation of Bruch's membrane in pathology. In INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE. Vancouver, CA: ROCKVILLE: ASSOC RESEARCH VISION OPHTHALMOLOGY INC.

MLA:

Schottenhamml, Julia, et al. "Deep learning based hybrid OCT-OCTA segmentation of Bruch's membrane in pathology." Proceedings of the Annual Meeting of the Association-for-Research-in-Vision-and-Ophthalmology (ARVO), Vancouver ROCKVILLE: ASSOC RESEARCH VISION OPHTHALMOLOGY INC, 2019.

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