Extraction of Exudates and Blood vessels in digital fundus images

被引:0
|
作者
Kande, Giri Babu [1 ]
Savithri, T. Satya [2 ]
Subbaiah, P. Venkata [3 ]
机构
[1] SRK Inst Technol, Vijayawada, Andhra Pradesh, India
[2] Jawaharlal Nehru Technol Univ, Hyderabad, Andhra Pradesh, India
[3] Amrita Sai Inst Sci & Technol, Paritala, Andhra Pradesh, India
关键词
D O I
10.1109/CIT.2008.4594730
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes two efficient approaches for automatic detection and extraction of Exudates and Blood vessels in ocular fundus images. The blood vessel extraction algorithm is composed of three steps, i.e., matched filtering, thresholding and label filtering. The identification of exudates involves Preprocessing, Optic disk elimination; and Segmentation of Exudates. In both the methods the enhanced segments are extracted based on Spatially Weighted Fuzzy c-Means (SWFCM) clustering algorithm. The Spatially Weighted Fuzzy c-Means clustering algorithm is formulated by incorporating the spatial neighborhood information into the standard FCM clustering algorithm. Experimental evaluations of both the approaches demonstrate superior performances over other vessel detection and exudates detection algorithms recently reported in the literature.
引用
收藏
页码:526 / +
页数:2
相关论文
共 50 条
  • [31] Automated analysis of the distributions and geometries of blood vessels on retinal fundus images
    Hatanaka, Y
    Hara, T
    Fujita, H
    Aoyama, M
    Uchida, H
    Yamamoto, T
    [J]. MEDICAL IMAGING 2004: IMAGE PROCESSING, PTS 1-3, 2004, 5370 : 1621 - 1628
  • [32] New algorithm for detecting smaller retinal blood vessels in fundus images
    LeAnder, Robert
    Bidari, Praveen I.
    Mohammed, Tauseef A.
    Das, Moumita
    Umbaugh, Scott E.
    [J]. MEDICAL IMAGING 2010: COMPUTER - AIDED DIAGNOSIS, 2010, 7624
  • [33] Detection of blood vessels in fundus images of the retina using Gabor wavelets
    Oloumi, Faraz
    Rangayyan, Rangaraj M.
    Oloumi, Foad
    Eshghzadeh-Zanjani, Peyman
    Ayres, Fabio J.
    [J]. 2007 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-16, 2007, : 6452 - 6455
  • [34] BLOOD VESSELS EXTRACTION FROM FUNDUS FLUORESCEIN ANGIOGRAM IN CURVELET DOMAIN
    Tehrani, Amir Ali Amini
    Ebrahimpour-komleh, Hossein
    Aghadoost, Davood
    [J]. 2018 6TH IRANIAN JOINT CONGRESS ON FUZZY AND INTELLIGENT SYSTEMS (CFIS), 2018, : 195 - 199
  • [35] DETECTION OF EXUDATES FROM DIGITAL FUNDUS IMAGES USING A REGION-BASED SEGMENTATION TECHNIQUE
    Jaafar, Hussain F.
    Nandi, Asoke K.
    Al-Nuaimy, Waleed
    [J]. 19TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO-2011), 2011, : 1020 - 1024
  • [36] Bin loss for hard exudates segmentation in fundus images
    Guo, Song
    Wang, Kai
    Kang, Hong
    Liu, Teng
    Gao, Yingqi
    Li, Tao
    [J]. NEUROCOMPUTING, 2020, 392 : 314 - 324
  • [37] Extraction of blood vessels and optic disc in retinal images
    Nimbarte, Nita
    Mushrif, Milind
    [J]. COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION, 2018, 6 (01): : 31 - 42
  • [38] Dilated Deep Neural Network for Segmentation of Retinal Blood Vessels in Fundus Images
    Biswas, Raj
    Vasan, Ashwin
    Roy, Sanjiban Sekhar
    [J]. IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF ELECTRICAL ENGINEERING, 2020, 44 (01) : 505 - 518
  • [39] Exudates and Blood Vessel Segmentation in Eye Fundus Images Using the Fourier and Cosine Discrete Transforms
    Lara Rodriguez, Luis David
    Urcid Serrano, Gonzalo
    [J]. COMPUTACION Y SISTEMAS, 2016, 20 (04): : 697 - 708
  • [40] Dilated Deep Neural Network for Segmentation of Retinal Blood Vessels in Fundus Images
    Raj Biswas
    Ashwin Vasan
    Sanjiban Sekhar Roy
    [J]. Iranian Journal of Science and Technology, Transactions of Electrical Engineering, 2020, 44 : 505 - 518