The application of deep learning framework in quantifying retinal structures on ophthalmic image in research eye-PACS

Moye Yu; Siliang Zhang; Brent J. Liu; Shenghui Zhao; Aimin Sang; Jiancheng Dong; Huiqun Wu

doi:10.1117/12.2512458

15 March 2019 The application of deep learning framework in quantifying retinal structures on ophthalmic image in research eye-PACS

Moye Yu, Siliang Zhang, Brent J. Liu, Shenghui Zhao, Aimin Sang, Jiancheng Dong, Huiqun Wu

Author Affiliations +

Proceedings Volume 10954, Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications; 1095402 (2019) https://doi.org/10.1117/12.2512458
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

The rise of deep learning (DL) framework and its application in object recognition could benefit image-based medical diagnosis. Since eye is believed to be a window into human health, the application of DL on differentiating abnormal ophthalmic photography (OP) will greatly empower ophthalmologists to relieve their workload for disease screening. In our previous work, we employed ResNet-50 to construct classification model for diabetic retinopathy(DR) within the PACS. In this study, we implemented latest DL object detection and semantic segmentation framework to empower the eye-PACS. Mask R-CNN framework was selected for object detection and instance segmentation of the optic disc (OD) and the macula. Furthermore, Unet framework was utilized for semantic segmentation of retinal vessel pixels from OP. The performance of the segmented results by two frameworks achieved state-of-art efficiency and the segmented results were transmitted to PACS as grayscale softcopy presentation state (GSPS) file. We also developed a prototype for OP quantitative analysis. It’s believed that the implementation of DL framework into the object recognition and analysis on OPs is meaningful and worth further investigation.

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Citation Download Citation

Moye Yu, Siliang Zhang, Brent J. Liu, Shenghui Zhao, Aimin Sang, Jiancheng Dong, and Huiqun Wu "The application of deep learning framework in quantifying retinal structures on ophthalmic image in research eye-PACS", Proc. SPIE 10954, Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications, 1095402 (15 March 2019); https://doi.org/10.1117/12.2512458

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