Localization of Optic Disc in Color Fundus Images

被引:0
|
作者
Joshi, Shilpa [1 ]
Karule, P. T. [1 ]
机构
[1] Navi Mumbai Yashwantrao Chavan Coll Engn, Lokmanya Tilak Coll Engn, Nagpur, Maharashtra, India
关键词
Fundus Images; Hough Transform; Optic disc; Retinal Images; RETINAL IMAGES; BLOOD-VESSELS; NERVE HEAD; IDENTIFICATION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The objective of Medical image analysis field is to develop computational tools which will assist quantification and visualization of interesting pathology and anatomical structures. Diabetic retinopathy is a medical condition where the ration is damaged because fluid leaks from blood vessels into the retina.. The detection of the optic disk and the quantitative analysis of the evolution of its shape and its size can bring clinical information of big importance. This paper describes a novel method for localization of the optic disk boundary of retinal images. The proposed method consists of two steps: in the first step, a circular region of interest is found by first isolating the brightest area in the image by means of contrast enhancement and in the second step, the Hough transform is used to detect the main normal circular feature, the optical disk within the positive horizontal gradient image within this region of interest. The technique is tested on publicly available DRIVE, diaretdb0, diaretdb1 databases and Live images form hospital. Results obtained by applying these are presented on GUI (Graphic User Interface). Initial results on a database of fundus images show that the proposed method is effective and favorable in relation to comparable techniques. The intention of using GUI as an automated detection program is to allow simple and easy access for doctors or nurses to perform quick analysis and observation without the need of programming skills. The proposed method achieves an average accuracy of 94.7 percentage for localization of optic disk.
引用
收藏
页码:178 / 186
页数:9
相关论文
共 50 条
  • [31] Fast detection of the optic disc and fovea in color fundus photographs
    Niemeijer, Meindert
    Abramoff, Michael D.
    van Ginneken, Bram
    [J]. MEDICAL IMAGE ANALYSIS, 2009, 13 (06) : 859 - 870
  • [32] Automatic Tracing of Optic Disc and Exudates from Color Fundus Images Using Fixed and Variable Thresholds
    Ahmed Wasif Reza
    C. Eswaran
    Subhas Hati
    [J]. Journal of Medical Systems, 2009, 33 : 73 - 80
  • [33] Automated fuzzy optic disc detection algorithm using branching of vessels and color properties in fundus images
    Nergiz, Mehmet
    Akin, Mehmet
    Yildiz, Abdulnasir
    Takes, Omer
    [J]. BIOCYBERNETICS AND BIOMEDICAL ENGINEERING, 2018, 38 (04) : 850 - 867
  • [34] Automatic Identification and Segmentation of Exudates and Optic Disc in Color Fundus Images of the Diabetic Retinopathy Human Retina
    Ganesan, P.
    Chelladurai, R.
    Sureshkumar, M.
    Sathish, B. S.
    Kalist, V.
    [J]. RESEARCH JOURNAL OF PHARMACEUTICAL BIOLOGICAL AND CHEMICAL SCIENCES, 2015, 6 (04): : 908 - 915
  • [35] Automatic Tracing of Optic Disc and Exudates from Color Fundus Images Using Fixed and Variable Thresholds
    Reza, Ahmed Wasif
    Eswaran, C.
    Hati, Subhas
    [J]. JOURNAL OF MEDICAL SYSTEMS, 2009, 33 (01) : 73 - 80
  • [36] Segmentation of Optic Disc in Fundus Images Using an Active Contour
    Elbalaoui, A.
    Ouadid, Y.
    Merbouha, A.
    [J]. JOURNAL OF ELECTRONIC COMMERCE IN ORGANIZATIONS, 2018, 16 (01) : 97 - 111
  • [37] Agreement among ophthalmologists in marking the optic disc and optic cup in fundus images
    Almazroa, Ahmed
    Alodhayb, Sami
    Osman, Essameldin
    Ramadan, Eslam
    Hummadi, Mohammed
    Dlaim, Mohammed
    Alkatee, Muhannad
    Raahemifar, Kaamran
    Lakshminarayanan, Vasudevan
    [J]. INTERNATIONAL OPHTHALMOLOGY, 2017, 37 (03) : 701 - 717
  • [38] ODGNet: a deep learning model for automated optic disc localization and glaucoma classification using fundus images
    Latif, Jahanzaib
    Tu, Shanshan
    Xiao, Chuangbai
    Rehman, Sadaqat Ur
    Imran, Azhar
    Latif, Yousaf
    [J]. SN APPLIED SCIENCES, 2022, 4 (04)
  • [39] Optic Disc Boundary and Vessel Origin Segmentation of Fundus Images
    Roychowdhury, Sohini
    Koozekanani, Dara D.
    Kuchinka, Sam N.
    Parhi, Keshab K.
    [J]. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2016, 20 (06) : 1562 - 1574
  • [40] ODGNet: a deep learning model for automated optic disc localization and glaucoma classification using fundus images
    Jahanzaib Latif
    Shanshan Tu
    Chuangbai Xiao
    Sadaqat Ur Rehman
    Azhar Imran
    Yousaf Latif
    [J]. SN Applied Sciences, 2022, 4