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利用视网膜眼底图像和深度学习技术实现长时航天飞行期间贫血的非侵入式监测。

A non-invasive approach to monitor anemia during long-duration spaceflight with retinal fundus images and deep learning.

机构信息

University College Dublin School of Medicine, Belfield, Dublin, Ireland.

University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States.

出版信息

Life Sci Space Res (Amst). 2022 May;33:69-71. doi: 10.1016/j.lssr.2022.04.004. Epub 2022 Apr 19.

DOI:10.1016/j.lssr.2022.04.004
PMID:35491031
Abstract

During spaceflight, astronauts can experience significantly higher levels of hemolysis. With future space missions exposing astronauts to longer periods of microgravity, such as missions to Mars, there will be a need to better understand this phenomenon. We have proposed that retinal fundus photography and deep learning may be utilized to help further understand this microgravity-induced, anemic process for future spaceflight. By utilizing astronaut and terrestrial analog metadata, a foundation can be built to develop an algorithm that allows for non-invasive retinal imaging to quantify hemoglobin levels and detect anemia during spaceflight. This approach would allow for a non-invasive retinal photograph that can be done frequently during spaceflight as opposed to an invasive blood draw and subsequent tests.

摘要

在太空飞行期间,宇航员可能会经历更高水平的溶血。随着未来的太空任务使宇航员暴露在更长时间的微重力环境下,例如前往火星的任务,我们需要更好地了解这种现象。我们已经提出,眼底摄影和深度学习可能被用于帮助进一步了解这种微重力引起的贫血过程。通过利用宇航员和地球模拟元数据,可以建立一个基础,开发一种算法,允许通过非侵入性视网膜成像来量化血红蛋白水平,并在太空飞行中检测贫血。这种方法将允许在太空飞行期间频繁进行非侵入性视网膜摄影,而不是进行侵入性的采血和随后的测试。

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