Retinal image assessment using bi-level adaptive morphological component analysis
作者：
Highlights：
• Our method analyzes retinal image to extract diagnostically helpful components of the retinal image.
• These components are considered very important in clinical decision making.
• This method is based on extension of MCA which benefits from the adaptive representation obtained via dictionary learning.
• Reported results confirmed the effectiveness of the proposed method in the separation of vessel and exudate components.
摘要
•Our method analyzes retinal image to extract diagnostically helpful components of the retinal image.•These components are considered very important in clinical decision making.•This method is based on extension of MCA which benefits from the adaptive representation obtained via dictionary learning.•Reported results confirmed the effectiveness of the proposed method in the separation of vessel and exudate components.
论文关键词：Bi-level adaptive morphological component analysis,Dictionary learning,Diabetic retinopathy image assessment
论文评审过程：Received 25 July 2018, Revised 25 July 2019, Accepted 26 July 2019, Available online 30 July 2019, Version of Record 14 August 2019.
论文官网地址：https://doi.org/10.1016/j.artmed.2019.07.010
