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基于光反馈干涉的散射介质中微血管血流成像的方法与局限:在人体皮肤中的应用。

Methods and Limits for Micro Scale Blood Vessel Flow Imaging in Scattering Media by Optical Feedback Interferometry: Application to Human Skin.

机构信息

LAAS-CNRS, Université de Toulouse, CNRS, INP-ENSEEIHT, 31400 Toulouse, France.

Centre for the Development of Sensors, Instruments and Systems, Universitat Politècnica deCatalunya (UPC-CD6), Rambla Sant Nebridi, 10, E08222 Terrassa, Spain.

出版信息

Sensors (Basel). 2021 Feb 11;21(4):1300. doi: 10.3390/s21041300.

DOI:10.3390/s21041300
PMID:33670276
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7918789/
Abstract

At the micrometric scale, vessels or skin capillaries network architecture can provide useful information for human health management. In this paper, from simulation to in vitro, we investigate some limits and interests of optical feedback interferometry (OFI) for blood flow imaging of skin vascularization. In order to analyze the tissue scattering effect on OFI performances, a series of skin-tissue simulating optical phantoms have been designed, fabricated and characterized. The horizontal (2D) and vertical (depth penetration) sensing resolution of the OFI sensor have been estimated. The experimental results that we present on this study are showing a very good accordance with theoretical models. In the case of a skin phantom of 0.5 mm depth with a scattering coefficient from 0 to 10.8 mm-1, the presented OFI system is able to distinguish a pair of micro fluidic channels (100 µm × 100 µm) spaced by 10 µm. Eventually, an in vivo test on human skin is presented and, for the first time using an OFI sensor, a 2D blood flow image of a vein located just beneath the skin is computed.

摘要

在微观尺度上,血管或皮肤毛细血管网络结构可以为人体健康管理提供有用的信息。在本文中,我们从模拟到体外实验,研究了光学反馈干涉(OFI)在皮肤血管化血流成像中的一些局限性和应用价值。为了分析组织散射对 OFI 性能的影响,我们设计、制作和表征了一系列皮肤组织模拟光学体模。估计了 OFI 传感器的水平(2D)和垂直(深度穿透)传感分辨率。我们在这项研究中呈现的实验结果与理论模型非常吻合。在深度为 0.5mm、散射系数为 0 至 10.8mm-1 的皮肤体模的情况下,所提出的 OFI 系统能够分辨出间隔为 10μm 的一对微流通道(100μm×100μm)。最后,我们展示了一项人体皮肤的体内测试,这是首次使用 OFI 传感器计算出位于皮肤下方的静脉的二维血流图像。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/4b1ae5671248/sensors-21-01300-g013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/09018068b8c5/sensors-21-01300-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/6b18b6de1cf5/sensors-21-01300-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/0acb9a88fde1/sensors-21-01300-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/2341023dc3e7/sensors-21-01300-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/cfa998f81656/sensors-21-01300-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/be1b6024b79a/sensors-21-01300-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/5e9649036625/sensors-21-01300-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/4b1ae5671248/sensors-21-01300-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/e4e5a00dc0c7/sensors-21-01300-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/25ea75dd7990/sensors-21-01300-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/bf639d73cdb1/sensors-21-01300-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/1e6dd93129fe/sensors-21-01300-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/9d0047f792e9/sensors-21-01300-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/09018068b8c5/sensors-21-01300-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/6b18b6de1cf5/sensors-21-01300-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/0acb9a88fde1/sensors-21-01300-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/2341023dc3e7/sensors-21-01300-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/cfa998f81656/sensors-21-01300-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/be1b6024b79a/sensors-21-01300-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/5e9649036625/sensors-21-01300-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e9d/7918789/4b1ae5671248/sensors-21-01300-g013.jpg

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本文引用的文献

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A Deep Learning Approach to Vascular Structure Segmentation in Dermoscopy Colour Images.深度学习在皮肤镜彩色图像血管结构分割中的应用。
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Optical feedback interferometry for microscale-flow sensing study: numerical simulation and experimental validation.
用于微尺度流量传感研究的光反馈干涉测量法:数值模拟与实验验证
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