JointRCNN: A Region-Based Convolutional Neural Network for Optic Disc and Cup Segmentation

doi:10.1109/TBME.2019.2913211

CORC > 宁波材料技术与工程研究所 > 中国科学院宁波材料技术与工程研究所 > 2020专题

	JointRCNN: A Region-Based Convolutional Neural Network for Optic Disc and Cup Segmentation
	Jiang, Yuming ; Duan, Lixin ; Cheng, Jun ; Gu, Zaiwang ; Xia, Hu ; Fu, Huazhu ; Li, Changsheng ; Liu, Jiang
刊名	IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
	2020
卷号	67 期号:2 页码:335-343
关键词	FUNDUS IMAGES NERVE HEAD GLAUCOMA PREVALENCE
DOI	10.1109/TBME.2019.2913211
英文摘要	Objective: The purpose of this paper is to propose a novel algorithm for joint optic disc and cup segmentation, which aids the glaucoma detection. Methods: By assuming the shapes of cup and disc regions to be elliptical, we proposed an end-to-end region-based convolutional neural network for joint optic disc and cup segmentation (referred to as JointRCNN). Atrous convolution is introduced to boost the performance of feature extraction module. In JointRCNN, disc proposal network (DPN) and cup proposal network (CPN) are proposed to generate bounding box proposals for the optic disc and cup, respectively. Given the prior knowledge that the optic cup is located in the optic disc, disc attention module is proposed to connect DPN and CPN, where a suitable bounding box of the optic disc is first selected and then continued to be propagated forward as the basis for optic cup detection in our proposed network. After obtaining the disc and cup regions, which are the inscribed ellipses of the corresponding detected bounding boxes, the vertical cup-to-disc ratio is computed and used as an indicator for glaucoma detection. Results: Comprehensive experiments clearly show that our JointRCNN model outperforms state-of-the-art methods for optic disc and cup segmentation task and glaucoma detection task. Conclusion: Joint optic disc and cup segmentation, which utilizes the connection between optic disc and cup, could improve the performance of optic disc and cup segmentation. Significance: The proposed method improves the accuracy of glaucoma detection. It is promising to be used for glaucoma screening.
学科主题	Engineering
内容类型	期刊论文
源URL	[http://ir.nimte.ac.cn/handle/174433/20084]
专题	2020专题
作者单位	1.Cheng, J (corresponding author), Chinese Acad Sci, Div Intelligent Med Imaging, Cixi Inst Biomed Engn, Ningbo 315201, Peoples R China. 2.Duan, LX (corresponding author), Univ Elect Sci & Technol China, Big Data Res Ctr, Chengdu 611731, Peoples R China.
推荐引用方式 GB/T 7714	Jiang, Yuming,Duan, Lixin,Cheng, Jun,et al. JointRCNN: A Region-Based Convolutional Neural Network for Optic Disc and Cup Segmentation[J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING,2020,67(2):335-343.
APA	Jiang, Yuming.,Duan, Lixin.,Cheng, Jun.,Gu, Zaiwang.,Xia, Hu.,...&Liu, Jiang.(2020).JointRCNN: A Region-Based Convolutional Neural Network for Optic Disc and Cup Segmentation.IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING,67(2),335-343.
MLA	Jiang, Yuming,et al."JointRCNN: A Region-Based Convolutional Neural Network for Optic Disc and Cup Segmentation".IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 67.2(2020):335-343.