Application of infrared imaging for monitoring retinal vascular network: an electric circuit analogy approach

Xunfei Zhou; Sheng-Jen Hsieh

doi:10.1117/12.2305570

14 May 2018 Application of infrared imaging for monitoring retinal vascular network: an electric circuit analogy approach

Xunfei Zhou, Sheng-Jen Hsieh

Author Affiliations +

Proceedings Volume 10661, Thermosense: Thermal Infrared Applications XL; 1066113 (2018) https://doi.org/10.1117/12.2305570
Event: SPIE Commercial + Scientific Sensing and Imaging, 2018, Orlando, FL, United States

Abstract

It is well established that diabetes is linked with changes in ocular hemodynamics and retinal microaneurysms. However, it is difficult to diagnose a microaneurysm in a retinal vascular network using a traditional eye exam. The hypothesis of this study is that an overflow in the retinal vascular network will result in a temperature increase, and a microaneurysm could create a local hot spot. Therefore, this work investigates the possibility of applying infrared thermography to detect abnormal blood flow. As a precursor to human or animal testing, an electrical resistance network was used to simulate blood flow (using an electrical circuit analogy). An electrical signal with varied frequencies and peak voltages was used as the heating source. An infrared camera was used to acquire thermography images from the electrical resistance network. Thermal characteristics of the network were able to be derived from the images, suggesting that a timedependent and spatially resolved temperature mapping can be obtained and quantitatively analyzed. Moreover, combined with numerical simulation, the effect of blood flow change on surface temperature variation was investigated. This approach provides a way to apply thermal infrared imaging in diagnosis of retinal vascular diseases.

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Xunfei Zhou and Sheng-Jen Hsieh "Application of infrared imaging for monitoring retinal vascular network: an electric circuit analogy approach", Proc. SPIE 10661, Thermosense: Thermal Infrared Applications XL, 1066113 (14 May 2018); https://doi.org/10.1117/12.2305570

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