Synthesis of annotated pathological retinal OCT data with pathology-induced deformations

Hristina Uzunova; Leonie Basso; Jan Ehrhardt; Heinz Handels

doi:10.1117/12.2611126

4 April 2022 Synthesis of annotated pathological retinal OCT data with pathology-induced deformations

Hristina Uzunova, Leonie Basso, Jan Ehrhardt, Heinz Handels

Proceedings Volume 12033, Medical Imaging 2022: Computer-Aided Diagnosis; 120333K (2022) https://doi.org/10.1117/12.2611126
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Abstract

In this work, a generative adversarial network (GAN)-based pipeline for the generation of realistic retinal optical coherence tomography (OCT) images with available pathological structures and ground truth anatomical and pathological annotations is established. The emphasis of the proposed image generation approach lies especially on the simulation of the pathology-induced deformations of the retinal layers around a pathological structure. Our experiments demonstrate the realistic appearance of the images as well as their applicability for the training of neural networks.

Conference Presentation

Citation Download Citation

Hristina Uzunova, Leonie Basso, Jan Ehrhardt, and Heinz Handels "Synthesis of annotated pathological retinal OCT data with pathology-induced deformations", Proc. SPIE 12033, Medical Imaging 2022: Computer-Aided Diagnosis, 120333K (4 April 2022); https://doi.org/10.1117/12.2611126

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