Automatic quality assessment and segmentation of diabetic retinopathy images

© 2016 IEEE. Diabetes is considered to be one of the most dangerous genetic disorders. It could cause the loss of sight in the case of the diabetic retinopathy. Several medical technologies have been developed and improved to cure the diabetes and overcome the lacks of human experts. This can be don...

Full description

Saved in:
Bibliographic Details
Main Authors: Worapan Kusakunniran, Jirat Rattanachoosin, Krittanat Sutassananon, Phuthimeth Anekkitphanich
Other Authors: Mahidol University
Format: Conference or Workshop Item
Published: 2018
Subjects:
Online Access:https://repository.li.mahidol.ac.th/handle/123456789/42374
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Mahidol University
id th-mahidol.42374
record_format dspace
spelling th-mahidol.423742019-03-14T15:03:25Z Automatic quality assessment and segmentation of diabetic retinopathy images Worapan Kusakunniran Jirat Rattanachoosin Krittanat Sutassananon Phuthimeth Anekkitphanich Mahidol University Computer Science Engineering © 2016 IEEE. Diabetes is considered to be one of the most dangerous genetic disorders. It could cause the loss of sight in the case of the diabetic retinopathy. Several medical technologies have been developed and improved to cure the diabetes and overcome the lacks of human experts. This can be done by replacing the manual process using human labors with the automatic diagnosis. In order to achieve this purpose, it requires two main steps which will be focused in this paper. They are the quality assessment and the segmentation of diabetic retinopathy images. In the image quality assessment, four features (namely color, contrast, focus, and illumination) have been investigated. As a result, the contrast histogram in the Principal Component Analysis (PCA) space is used. In the image segmentation, the histogram equalization is used in the pre-processing. Then, the image segmentation based on the iterative selection and the grabcut algorithm is applied. The experimental results demonstrate that the proposed method can achieve very promising performance. 2018-12-21T07:22:22Z 2019-03-14T08:03:25Z 2018-12-21T07:22:22Z 2019-03-14T08:03:25Z 2017-02-08 Conference Paper IEEE Region 10 Annual International Conference, Proceedings/TENCON. (2017), 997-1000 10.1109/TENCON.2016.7848155 21593450 21593442 2-s2.0-85015407142 https://repository.li.mahidol.ac.th/handle/123456789/42374 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85015407142&origin=inward
institution Mahidol University
building Mahidol University Library
continent Asia
country Thailand
Thailand
content_provider Mahidol University Library
collection Mahidol University Institutional Repository
topic Computer Science
Engineering
spellingShingle Computer Science
Engineering
Worapan Kusakunniran
Jirat Rattanachoosin
Krittanat Sutassananon
Phuthimeth Anekkitphanich
Automatic quality assessment and segmentation of diabetic retinopathy images
description © 2016 IEEE. Diabetes is considered to be one of the most dangerous genetic disorders. It could cause the loss of sight in the case of the diabetic retinopathy. Several medical technologies have been developed and improved to cure the diabetes and overcome the lacks of human experts. This can be done by replacing the manual process using human labors with the automatic diagnosis. In order to achieve this purpose, it requires two main steps which will be focused in this paper. They are the quality assessment and the segmentation of diabetic retinopathy images. In the image quality assessment, four features (namely color, contrast, focus, and illumination) have been investigated. As a result, the contrast histogram in the Principal Component Analysis (PCA) space is used. In the image segmentation, the histogram equalization is used in the pre-processing. Then, the image segmentation based on the iterative selection and the grabcut algorithm is applied. The experimental results demonstrate that the proposed method can achieve very promising performance.
author2 Mahidol University
author_facet Mahidol University
Worapan Kusakunniran
Jirat Rattanachoosin
Krittanat Sutassananon
Phuthimeth Anekkitphanich
format Conference or Workshop Item
author Worapan Kusakunniran
Jirat Rattanachoosin
Krittanat Sutassananon
Phuthimeth Anekkitphanich
author_sort Worapan Kusakunniran
title Automatic quality assessment and segmentation of diabetic retinopathy images
title_short Automatic quality assessment and segmentation of diabetic retinopathy images
title_full Automatic quality assessment and segmentation of diabetic retinopathy images
title_fullStr Automatic quality assessment and segmentation of diabetic retinopathy images
title_full_unstemmed Automatic quality assessment and segmentation of diabetic retinopathy images
title_sort automatic quality assessment and segmentation of diabetic retinopathy images
publishDate 2018
url https://repository.li.mahidol.ac.th/handle/123456789/42374
_version_ 1763492911734849536