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Abstract #90187 Published in IGR 21-3
Optic disc and optic cup segmentation based on anatomy guided cascade network
Bian X; Luo X; Wang C; Liu W; Lin XComputer Methods and Programs in Biomedicine 2020; 197: 105717
BACKGROUND AND OBJECTIVE: Glaucoma, a worldwide eye disease, may cause irreversible vision damage. If not treated properly at an early stage, glaucoma eventually deteriorates into blindness. Various glaucoma screening methods, e.g. Ultrasound Biomicroscopy (UBM), Optical Coherence Tomography (OCT), and Heidelberg Retinal Scanner (HRT), are available. However, retinal fundus image photography examination, because of its low cost, is one of the most common solutions used to diagnose glaucoma. Clinically, the cup-to-disk ratio is an important indicator in glaucoma diagnosis. Therefore, precise fundus image segmentation to calculate the cup-to-disk ratio is the basis for screening glaucoma. METHODS: In this paper, we propose a deep neural network that uses anatomical knowledge to guide the segmentation of fundus images, which accurately segments the optic cup and the optic disc in a fundus image to accurately calculate the cup-to-disk ratio. Optic disc and optic cup segmentation are typical small target segmentation problems in biomedical images. We propose to use an attention-based cascade network to effectively accelerate the convergence of small target segmentation during training and accurately reserve detailed contours of small targets. RESULTS: Our method, which was validated in the MICCAI REFUGE fundus image segmentation competition, achieves 93.31% dice score in optic disc segmentation and 88.04% dice score in optic cup segmentation. Moreover, we win a high CDR evaluation score, which is useful for glaucoma screening. CONCLUSIONS: The proposed method successfully introduce anatomical knowledge into segmentation task, and achieve state-of-the-art performance in fundus image segmentation. It also can be used for both automatic segmentation and semiautomatic segmentation with human interaction.
Fujian Key Laboratory of Sensing and Computing for Smart Cities, Department of Computer Science, School of Informatics, Xiamen University, Xiamen 361005, China.
Full articleClassification:
6.30 Other (Part of: 6 Clinical examination methods)
6.8.2 Posterior segment (Part of: 6 Clinical examination methods > 6.8 Photography)
2.14 Optic disc (Part of: 2 Anatomical structures in glaucoma)
