Self-supervised multimodal reconstruction of retinal images over paired datasets

作者:

Highlights:

• Self-supervised multimodal reconstruction tasks are enabled through image registration.

• Non-invasive deep learning pseudo-angiographies are generated from retinographies.

• The generated pseudo-angiographies resemble the original angiographies.

• Generating angiography images requires the recognition of high-level retinal patterns.

• Multimodal reconstruction provides relevant domain information without human labels.

摘要

•Self-supervised multimodal reconstruction tasks are enabled through image registration.•Non-invasive deep learning pseudo-angiographies are generated from retinographies.•The generated pseudo-angiographies resemble the original angiographies.•Generating angiography images requires the recognition of high-level retinal patterns.•Multimodal reconstruction provides relevant domain information without human labels.

论文关键词:Self-supervised learning,Eye fundus,Deep learning,Multimodal,Retinography,Angiography

论文评审过程:Received 13 January 2020, Revised 27 April 2020, Accepted 16 June 2020, Available online 26 June 2020, Version of Record 8 July 2020.

论文官网地址:https://doi.org/10.1016/j.eswa.2020.113674