Automatic Optic Disc Detection From Retinal Images by a Line Operator

被引:85
|
作者
Lu, Shijian [1 ]
Lim, Joo Hwee [1 ]
机构
[1] ASTAR, Dept Comp Vis & Image Understanding, Inst Infocomm Res, Singapore 138632, Singapore
关键词
Computer-aided diagnosis; line operators; optic disc (OD) detection; retinal image analysis; DIABETIC-RETINOPATHY; VESSEL SEGMENTATION; FUNDUS IMAGES; LOCALIZATION; DIAGNOSIS; NERVE; MODEL;
D O I
10.1109/TBME.2010.2086455
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Under the framework of computer-aided eye disease diagnosis, this paper presents an automatic optic disc (OD) detection technique. The proposed technique makes use of the unique circular brightness structure associated with the OD, i.e., the OD usually has a circular shape and is brighter than the surrounding pixels whose intensity becomes darker gradually with their distances from the OD center. A line operator is designed to capture such circular brightness structure, which evaluates the image brightness variation along multiple line segments of specific orientations that pass through each retinal image pixel. The orientation of the line segment with the minimum/maximum variation has specific pattern that can be used to locate the OD accurately. The proposed technique has been tested over four public datasets that include 130, 89, 40, and 81 images of healthy and pathological retinas, respectively. Experiments show that the designed line operator is tolerant to different types of retinal lesion and imaging artifacts, and an average OD detection accuracy of 97.4% is obtained.
引用
收藏
页码:88 / 94
页数:7
相关论文
共 50 条
  • [31] Automatic Optic Disc Detection in Digital Fundus Images Using Image Processing
    Akhade, Snehal B.
    Deshmukh, V. U.
    Deosarkar, S. B.
    2014 INTERNATIONAL CONFERENCE ON GREEN COMPUTING COMMUNICATION AND ELECTRICAL ENGINEERING (ICGCCEE), 2014,
  • [32] Contrast based circular approximation for accurate and robust optic disc segmentation in retinal images
    Sigut, Jose
    Nunez, Omar
    Fumero, Francisco
    Gonzalez, Marta
    Arnay, Rafael
    PEERJ, 2017, 5
  • [33] Automatic Optic Disc Detection in Retinal Images via Group Sparse Regularization Extreme Learning Machine
    Zhou, Wei
    Wu, Chengdong
    Du, Wenyou
    PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017), 2017, : 11053 - 11058
  • [34] Automatic optic disk detection in retinal images using hybrid vessel phase portrait analysis
    Muangnak, Nittaya
    Aimmanee, Pakinee
    Makhanov, Stanislav
    MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, 2018, 56 (04) : 583 - 598
  • [35] Automatic Segmentation of Optic Disk in Retinal Images using DWT
    Bharkad, Sangita
    2016 IEEE 6TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING (IACC), 2016, : 386 - 391
  • [36] Parapapillary atrophy and optic disc region assessment (PANDORA): retinal imaging tool for assessment of the optic disc and parapapillary atrophy
    Lu, Cheng-Kai
    Tang, Tong Boon
    Laude, Augustinus
    Dhillon, Baljean
    Murray, Alan F.
    JOURNAL OF BIOMEDICAL OPTICS, 2012, 17 (10)
  • [37] Automatic Localization of the Optic Disc in Retinal Fundus Images Using Multiple Features
    Qureshi, Touseef Ahmad
    Amin, Hassan
    Hussain, Mahfooz
    Qureshi, Rashid Jalal
    Al-Diri, Bashir
    IEEE 12TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS & BIOENGINEERING, 2012, : 488 - 493
  • [38] A new approach to optic disc detection in human retinal images using the firefly algorithm
    Rahebi, Javad
    Hardalac, Firat
    MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, 2016, 54 (2-3) : 453 - 461
  • [39] Automatic detection of exudates and optic disk in retinal images using curvelet transform
    Esmaeili, M.
    Rabbani, H.
    Dehnavi, A. M.
    Dehghani, A.
    IET IMAGE PROCESSING, 2012, 6 (07) : 1005 - 1013
  • [40] Optic Disc Boundary Detection from Digital Fundus Images
    Hashim, F. A.
    Salem, N. M.
    Seddik, A. F.
    JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2015, 5 (01) : 50 - 56