Automated Segmentation Methods of Drusen to Diagnose Age-Related Macular Degeneration Screening in Retinal Images
Joint Authors
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-03-12
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Existing drusen measurement is difficult to use in clinic because it requires a lot of time and effort for visual inspection.
In order to resolve this problem, we propose an automatic drusen detection method to help clinical diagnosis of age-related macular degeneration.
First, we changed the fundus image to a green channel and extracted the ROI of the macular area based on the optic disk.
Next, we detected the candidate group using the difference image of the median filter within the ROI.
We also segmented vessels and removed them from the image.
Finally, we detected the drusen through Renyi’s entropy threshold algorithm.
We performed comparisons and statistical analysis between the manual detection results and automatic detection results for 30 cases in order to verify validity.
As a result, the average sensitivity was 93.37% (80.95%~100%) and the average DSC was 0.73 (0.3~0.98).
In addition, the value of the ICC was 0.984 (CI: 0.967~0.993, p<0.01), showing the high reliability of the proposed automatic method.
We expect that the automatic drusen detection helps clinicians to improve the diagnostic performance in the detection of drusen on fundus image.
American Psychological Association (APA)
Kim, Young Jae& Kim, Kwang Gi. 2018. Automated Segmentation Methods of Drusen to Diagnose Age-Related Macular Degeneration Screening in Retinal Images. Computational and Mathematical Methods in Medicine،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1132071
Modern Language Association (MLA)
Kim, Young Jae& Kim, Kwang Gi. Automated Segmentation Methods of Drusen to Diagnose Age-Related Macular Degeneration Screening in Retinal Images. Computational and Mathematical Methods in Medicine No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1132071
American Medical Association (AMA)
Kim, Young Jae& Kim, Kwang Gi. Automated Segmentation Methods of Drusen to Diagnose Age-Related Macular Degeneration Screening in Retinal Images. Computational and Mathematical Methods in Medicine. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1132071
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132071