Proceedings | |
Learning Retinal Patterns from Multimodal Images | |
Novo, Jorge1  Hervella, Ãlvaro S.2  Rouco, José3  Ortega, Marcos4  | |
[1] Author to whom correspondence should be addressed.;CITICâResearch Center of Information and Communication Technologies, University of A Coruña, 17051 A Coruña, Spain;Department of Computer Science, University of A Coruña, 17051 A Coruña, Spain;Presented at the XoveTIC Congress, A Coruña, Spain, 27â28 September 2018. | |
关键词: self-supervised; multimodal; retinography; angiography; | |
DOI : 10.3390/proceedings2181195 | |
学科分类:社会科学、人文和艺术(综合) | |
来源: mdpi | |
【 摘 要 】
The training of deep neural networks usually requires a vast amount of annotated data, which is expensive to obtain in clinical environments. In this work, we propose the use of complementary medical image modalities as an alternative to reduce the required annotated data. The self-supervised training of a reconstruction task between paired multimodal images can be used to learn about the image contents without using any label. Experiments performed with the multimodal setting formed by retinography and fluorescein angiography demonstrate that the proposed task produces the recognition of relevant retinal structures.
【 授权许可】
CC BY
【 预 览 】
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RO201910256661226ZK.pdf | 1052KB | download |