Diabetic macular edema grading in retinal images using vector quantization and semi-supervised learning.

Journal: Technology and health care : official journal of the European Society for Engineering and Medicine

Published Date: Jan 1, 2018

Abstract

BACKGROUND: Diabetic macular edema (DME) is one of the severe complication of diabetic retinopathy causing severe vision loss and leads to blindness in severe cases if left untreated.

Authors

Fulong Ren

College of Computer Science and Engineering, Northeastern University, Shenyang, China; Key Laboratory of Medical Image Computing of Ministry of Education, Northeastern University, Shenyang, China.
Peng Cao

Medical Image Computing Laboratory of Ministry of Education, Northeastern University, 110819, Shenyang, China.
Dazhe Zhao

Medical Image Computing Laboratory of Ministry of Education, Northeastern University, 110819, Shenyang, China.
Chao Wan

The First Affiliated Hospital, Wannan Medical College, Wuhu, Anhui, China.

Keywords

Diabetic Retinopathy Exudates and Transudates Humans Image Interpretation, Computer-Assisted Macular Edema Sensitivity and Specificity Severity of Illness Index Supervised Machine Learning

External Resources

View on PubMed Access via DOI PubMed (29689762)

Diabetic macular edema grading in retinal images using vector quantization and semi-supervised learning.

Abstract

Authors

Keywords

External Resources

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