Automated Detection of Red Lesions Using Superpixel Multichannel Multifeature
Joint Authors
Chen, Dali
Yi, Yugen
Zhou, Wei
Wu, Chengdong
Wang, Zhenzhu
Du, Wenyou
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-04-23
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Red lesions can be regarded as one of the earliest lesions in diabetic retinopathy (DR) and automatic detection of red lesions plays a critical role in diabetic retinopathy diagnosis.
In this paper, a novel superpixel Multichannel Multifeature (MCMF) classification approach is proposed for red lesion detection.
In this paper, firstly, a new candidate extraction method based on superpixel is proposed.
Then, these candidates are characterized by multichannel features, as well as the contextual feature.
Next, FDA classifier is introduced to classify the red lesions among the candidates.
Finally, a postprocessing technique based on multiscale blood vessels detection is modified for removing nonlesions appearing as red.
Experiments on publicly available DiaretDB1 database are conducted to verify the effectiveness of our proposed method.
American Psychological Association (APA)
Zhou, Wei& Wu, Chengdong& Chen, Dali& Wang, Zhenzhu& Yi, Yugen& Du, Wenyou. 2017. Automated Detection of Red Lesions Using Superpixel Multichannel Multifeature. Computational and Mathematical Methods in Medicine،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1142448
Modern Language Association (MLA)
Zhou, Wei…[et al.]. Automated Detection of Red Lesions Using Superpixel Multichannel Multifeature. Computational and Mathematical Methods in Medicine No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1142448
American Medical Association (AMA)
Zhou, Wei& Wu, Chengdong& Chen, Dali& Wang, Zhenzhu& Yi, Yugen& Du, Wenyou. Automated Detection of Red Lesions Using Superpixel Multichannel Multifeature. Computational and Mathematical Methods in Medicine. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1142448
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142448