Automatic Microaneurysm Detection Using the Sparse Principal Component Analysis-Based Unsupervised Classification Method

Automatic Microaneurysm Detection Using the Sparse Principal Component Analysis-Based Unsupervised Classification Method

Since microaneurysms (MAs) can be seen as the earliest lesions in diabetic retinopathy, its detection plays a critical role in the diabetic retinopathy diagnosis. In recent years, many machine-learning methods have been developed for MA detection. Generally, MA candidates are first identified and th...

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Bibliographic Details
Main Authors: Wei Zhou, Chengdong Wu, Dali Chen, Yugen Yi, Wenyou Du
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Diabetic retinopathy
microaneurysm detection
sparse PCA
unsupervised classification
Online Access:https://ieeexplore.ieee.org/document/7859305/

Internet

https://ieeexplore.ieee.org/document/7859305/

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