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Chin. Opt. Lett.
 Home  List of Issues    Issue 11 , Vol. 15 , 2017    10.3788/COL201715.111701

Monte Carlo light transport-based blood vessel quantification using linear array photoacoustic tomography
Xiangwei Lin, Mingjian Sun, Naizhang Feng, Depeng Hu, and Yi Shen
Department of Control Science and Engineering, [Harbin Institute of Technology], Harbin 150001, China

Chin. Opt. Lett., 2017, 15(11): pp.111701

Topic:Medical optics and biotechnology
Keywords(OCIS Code): 170.5120  100.3020  110.5120  170.0110  

Photoacoustic tomography is a noninvasive and nonionized biomedical imaging modality but it cannot reveal the inner structure and sideward boundary information of blood vessels in the linear array detection mode. In contrast, Monte Carlo (MC) light transport could provide the optical fluence distribution around the entire vascular area. This research explores the combination of linear array transducer-based photoacoustic tomography and MC light transport in the blood vessel quantification. Simulation, phantom, and in vivo experiments are in good correlation with the ultrasound imaging, validating this approach can clearly visualize the internal region of blood vessels from background tissue.

Copyright: © 2003-2012 . This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Posted online:2017/8/23

Get Citation: Xiangwei Lin, Mingjian Sun, Naizhang Feng, Depeng Hu, and Yi Shen, "Monte Carlo light transport-based blood vessel quantification using linear array photoacoustic tomography," Chin. Opt. Lett. 15(11), 111701(2017)

Note: This work was partially supported by the National Natural Science Foundation of China (Nos. 61371045 and 11574064), the Shenzhen Science & Technology Program, China (No. JCYJ20160429115309834), the Science and Technology Development Plan Project of Shandong Province, China (Nos. 2015GGX103016 and 2016GGX103032), and the China Postdoctoral Science Foundation (No. 2015M571413). The authors are particularly grateful to Prof. Liang Song’s lab at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Science, for the support.


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