Conditional GAN for Prediction of Glaucoma Progression with Macular Optical Coherence Tomography

Hassan ON, Sahin S, Mohammadzadeh V, Yang X, Amini N, Mylavarapu A, Martinyan J, Hong T, Mahmoudinezhad G, Rueckert D, Nouri-Mahdavi K, Scalzo F (2020)


Publication Type: Conference contribution

Publication year: 2020

Journal

Publisher: Springer Science and Business Media Deutschland GmbH

Book Volume: 12510 LNCS

Pages Range: 761-772

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: San Diego, USA

ISBN: 9783030645588

DOI: 10.1007/978-3-030-64559-5_61

Abstract

The estimation of glaucoma progression is a challenging task as the rate of disease progression varies among individuals in addition to other factors such as measurement variability and the lack of standardization in defining progression. Structural tests, such as thickness measurements of the retinal nerve fiber layer or the macula with optical coherence tomography (OCT), are able to detect anatomical changes in glaucomatous eyes. Such changes may be observed before any functional damage. In this work, we built a generative deep learning model using the conditional GAN architecture to predict glaucoma progression over time. The patient’s OCT scan is predicted from three or two prior measurements. The predicted images demonstrate high similarity with the ground truth images. In addition, our results suggest that OCT scans obtained from only two prior visits may actually be sufficient to predict the next OCT scan of the patient after six months.

Involved external institutions

How to cite

APA:

Hassan, O.N., Sahin, S., Mohammadzadeh, V., Yang, X., Amini, N., Mylavarapu, A.,... Scalzo, F. (2020). Conditional GAN for Prediction of Glaucoma Progression with Macular Optical Coherence Tomography. In George Bebis, Zhaozheng Yin, Edward Kim, Jan Bender, Kartic Subr, Bum Chul Kwon, Jian Zhao, Denis Kalkofen, George Baciu (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 761-772). San Diego, USA: Springer Science and Business Media Deutschland GmbH.

MLA:

Hassan, Osama N., et al. "Conditional GAN for Prediction of Glaucoma Progression with Macular Optical Coherence Tomography." Proceedings of the 15th International Symposium on Visual Computing, ISVC 2020, San Diego, USA Ed. George Bebis, Zhaozheng Yin, Edward Kim, Jan Bender, Kartic Subr, Bum Chul Kwon, Jian Zhao, Denis Kalkofen, George Baciu, Springer Science and Business Media Deutschland GmbH, 2020. 761-772.

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