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뇌과학이미징연구단
뇌과학 이미징 연구단
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Geographic atrophy segmentation in SD-OCT images using synthesized fundus autofluorescence imaging

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Title
Geographic atrophy segmentation in SD-OCT images using synthesized fundus autofluorescence imaging
Author(s)
Menglin Wu; Xinxin Cai; Qiang Chen; Zexuan Ji; Sijie Niu; Theodore Leng; Daniel L. Rubin; Hyunjin Park
Publication Date
2019-12
Journal
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, v.182, no., pp.105101 -
Publisher
ELSEVIER IRELAND LTD
Abstract
© 2019Background and objective: Accurate assessment of geographic atrophy (GA) is critical for diagnosis and therapy of non-exudative age-related macular degeneration (AMD). Herein, we propose a novel GA segmentation framework for spectral-domain optical coherence tomography (SD-OCT) images that employs synthesized fundus autofluorescence (FAF) images. Methods: An en-face OCT image is created via the restricted sub-volume projection of three-dimensional OCT data. A GA region-aware conditional generative adversarial network is employed to generate a plausible FAF image from the en-face OCT image. The network balances the consistency between the entire synthesize FAF image and the lesion. We use a fully convolutional deep network architecture to segment the GA region using the multimodal images, where the features of the en-face OCT and synthesized FAF images are fused on the front-end of the network. Results: Experimental results for 56 SD-OCT scans with GA indicate that our synthesis algorithm can generate high-quality synthesized FAF images and that the proposed segmentation network achieves a dice similarity coefficient, an overlap ratio, and an absolute area difference of 87.2%, 77.9%, and 11.0%, respectively. Conclusion: We report an automatic GA segmentation method utilizing synthesized FAF images. Significance: Our method is effective for multimodal segmentation of the GA region and can improve AMD treatment
URI
https://pr.ibs.re.kr/handle/8788114/6403
ISSN
0169-2607
Appears in Collections:
Center for Neuroscience Imaging Research (뇌과학 이미징 연구단) > Journal Papers (저널논문)
Files in This Item:
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