Fast Detection of Microaneurysms in Color Fundus Images

被引：0
|
作者：
Chen, Sean H. F. [1 ]
Hsiao, Han C. W. [1 ]
机构：
[1] Asia Univ, Dept Bioinformat & Med Engn, Taichung, Taiwan
来源：
2016 IEEE SECOND INTERNATIONAL CONFERENCE ON MULTIMEDIA BIG DATA (BIGMM) | 2016年
关键词：
microaneurysm detection; fundus image; AUTOMATIC DETECTION; DIABETIC-RETINOPATHY; PHOTOGRAPHS; RETINA; TRANSFORM;
D O I：
10.1109/BigMM.2016.65
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Diabetic retinopathy is known to be one of the most frequent and serious eye diseases that typically cause blindness in adults between 20 and 60 years of age. Microaneurysm (MA) is one of the most important syndromes in color fundus images. A tool for automatic detection of MAs can significantly reduce the workload of the ophthalmologists. A multi-stage strategy to screen candidate MAs is used in this study. The computation time for screening one fundus image of size 1500x1152 is 16.8 seconds. Ten verified MAs are successfully detected. Another 5 putative spots need to be verified. The result demonstrates that the proposed approach is efficient yet effective.
引用
收藏
页码：365 / 371
页数：7
相关论文
共 50 条
  • [11] Automatic Detection of Microaneurysms and Hemorrhages in Digital Fundus Images
    Giri Babu Kande
    T. Satya Savithri
    P. Venkata Subbaiah
    [J]. Journal of Digital Imaging, 2010, 23 : 430 - 437
  • [12] An efficient microaneurysms detection approach in retinal fundus images
    Mohan, N. Jagan
    Murugan, R.
    Goel, Tripti
    Tanveer, M.
    Roy, Parthapratim
    [J]. INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2023, 14 (04) : 1235 - 1252
  • [13] Automatic Detection of Microaneurysms and Hemorrhages in Digital Fundus Images
    Kande, Giri Babu
    Savithri, T. Satya
    Subbaiah, P. Venkata
    [J]. JOURNAL OF DIGITAL IMAGING, 2010, 23 (04) : 430 - 437
  • [14] Detection of Microaneurysms in Fundus Images Based on an Attention Mechanism
    Zhang, Lizong
    Feng, Shuxin
    Duan, Guiduo
    Li, Ying
    Liu, Guisong
    [J]. GENES, 2019, 10 (10)
  • [15] Automatic detection of microaneurysms in color fundus images of the human retina by means of the bounding box closing
    Walter, T
    Klein, JC
    [J]. MEDICAL DATA ANALYSIS, PROCEEDINGS, 2002, 2526 : 210 - 220
  • [16] Microaneurysms detection in color fundus images using machine learning based on directional local contrast
    Shengchun Long
    Jiali Chen
    Ante Hu
    Haipeng Liu
    Zhiqing Chen
    Dingchang Zheng
    [J]. BioMedical Engineering OnLine, 19
  • [17] Microaneurysms detection in color fundus images using machine learning based on directional local contrast
    Long, Shengchun
    Chen, Jiali
    Hu, Ante
    Liu, Haipeng
    Chen, Zhiqing
    Zheng, Dingchang
    [J]. BIOMEDICAL ENGINEERING ONLINE, 2020, 19 (01)
  • [18] Automated Detection of Microaneurysms in Color Fundus Images using Deep Learning with Different Preprocessing Approaches
    Tavakoli, Meysam
    Jazani, Sina
    Nazar, Mandieh
    [J]. MEDICAL IMAGING 2020: IMAGING INFORMATICS FOR HEALTHCARE, RESEARCH, AND APPLICATIONS, 2020, 11318
  • [19] Automatic detection of microaneurysms in diabetic retinopathy fundus images using the L*a*b color space
    Navarro, Pedro J.
    Alonso, Diego
    Stathis, Kostas
    [J]. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 2016, 33 (01) : 74 - 83
  • [20] Edge directed inference for microaneurysms detection in digital fundus images
    Huang, Ke
    Yan, Michelle
    Aviyente, Selin
    [J]. MEDICAL IMAGING 2007: IMAGE PROCESSING, PTS 1-3, 2007, 6512
12345