Diabetic retinopathy detection through novel tetragonal local octa patterns and extreme learning machines

作者：

Highlights：

• A method to detect various stages of the diabetic retinopathy(DR) is proposed.

• For feature extraction, tetragonal local octal patterns (T-LOP) are introduced.

• Classification for DR stages is done through the extreme learning machine (ELM).

• Performance of the proposed method is evaluated over the large-scale DR-datasets.

摘要

•A method to detect various stages of the diabetic retinopathy(DR) is proposed.•For feature extraction, tetragonal local octal patterns (T-LOP) are introduced.•Classification for DR stages is done through the extreme learning machine (ELM).•Performance of the proposed method is evaluated over the large-scale DR-datasets.

论文关键词：Diabetic retinopathy,Tetragonal local octa patterns,Extreme learning machines,Content based image retrieval

论文评审过程：Received 2 November 2018, Revised 17 January 2019, Accepted 15 July 2019, Available online 26 July 2019, Version of Record 14 August 2019.

论文官网地址：https://doi.org/10.1016/j.artmed.2019.07.003