E12 - Synthesis of Diabetic Retina Fundus Images Using Semantic Label Generation

Joon-Ho Son, Amir Alansary, Daniel Rueckert, Bernhard Kainz, Benjamin Hou

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Automatic segmentation of retina lesions have been a long standing and challenging task for learning based models, mostly due to the lack of available and accurate lesion segmentation datasets. In this paper, we propose a two-step process for generating photo-realistic fundus images conditioned on synthetic \"ground truth\" semantic labels, and demonstrate its potential for further downstream tasks, such as, but not limited to; automated grading of diabetic retinopathy, dataset balancing, creating image examples for trainee ophthalmologists, etc.
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Thursday 8th July
E4-12 (short): Image Registration / Synthesis - 13:45 - 14:30 (UTC+2)
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