A lightweight real-time smartphone-based laser speckle contrast analyzer

Recently, laser speckle contrast analysis (LASCA) technology has spurred the exploration to instantly visualize microcirculatory tissue blood perfusion in clinical diagnosis, due to its non-contact, non-invasive and rapid imaging advantages. However, traditional medical imaging systems used to perfo...

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Veröffentlicht in:Optics communications 2023-09, Vol.543, p.129613, Article 129613
Hauptverfasser: Wu, Zhenhai, Cao, Yuan, Waris, Haroon, Yao, Enyi, Liang, Dong
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Sprache:eng
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Zusammenfassung:Recently, laser speckle contrast analysis (LASCA) technology has spurred the exploration to instantly visualize microcirculatory tissue blood perfusion in clinical diagnosis, due to its non-contact, non-invasive and rapid imaging advantages. However, traditional medical imaging systems used to perform laser speckle contrast imaging (LSCI) are expensive and their transportation needs prudence, limiting the wide availability of LASCA for personal preliminary diagnosis. In this article, a low-cost, lightweight and portable smartphone-based laser speckle contrast imaging (smartphone-LSCI) is proposed to address this issue. With a built-in image sensor and powerful computational capability of the smartphone, the proposed system could be utilized to estimate the speckle contrast of human skin under various conditions and obtain information of the blood flow velocity of capillaries along with the degree of blood perfusion. Through experiments and theoretical analysis, we systematically studied the feasibility and robustness of image sensors on smartphones-LSCI. Experiments prove that ambient light has little influence on the performance of our smartphone-LSCI. In addition, the speckle image processing flow of smartphone-LSCI is proposed, together with an enhanced spatial LASCA (esLASCA) method. In the experiments with a low-cost smartphone, i.e., Redmi K40, the 4000×3000 pixels images can be processed at a frame rate of 20Hz. The consumption time of both the existing state-of-the-art roll algorithm and the proposed esLASCA is linearly proportional to the width (height) of the image resolution. However, our proposed method shows a slower growth rate and lower computational time when the window size is small.
ISSN:0030-4018
1873-0310
DOI:10.1016/j.optcom.2023.129613