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Enhancement of objects in photoacoustic tomography using selective filtering

Issue title: Frontiers in Biomedical Engineering and Biotechnology – Proceedings of the 4th International Conference on Biomedical Engineering and Biotechnology, 18–21 August 2015, Shanghai, China

Guest editors: Feng Liu, Dong-Hoon Lee, Ricardo Lagoa and Sandeep Kumar

Article type: Research Article

Authors: Shin, Dong-hoa | Yang, Yoonseokb | Song, Chul-Gyua; c; *

Affiliations: [a] Department of Electronic Engineering, Chonbuk National University, Jeonju-si, Jeonbuk, Korea | [b] Division of Biomedical Engineering, Chonbuk National University, Jeonju-si, Jeonbuk, Korea | [c] Center for Advanced Bioimaging Research, Chonbuk National University, Jeonju-si, Jeonbuk, Korea

Correspondence: [*] Address for correspondence: Chul-Gyu Song, Electronic Engineering Department, Chonbuk National University, 66-14 Deok jin-dong, Jeonju-si, Jeonbuk, Korea. Tel.: +82 63 270 4282; E-mail: [email protected].

Note: [1] Dong-ho Shin and Yoonseok Yang contributed equally to this work.

Keywords: Photoacoustic image, real-time, back projection algorithm, ultrasonic imaging, selective filtering

DOI: 10.3233/BME-151419

Journal: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1223-S1230, 2015

Published: 2015
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Here we developed a real-time photoacoustic tomography (PAT) imaging acquisition device based on the linear array transducer utilized on ultrasonic devices. Also, we produced a phantom including diverse contrast media and acquired PAT imaging as the light source wavelength was changing to see if the contrast media reacted. Indocyanine green showed the highest reaction around the 800-nm band, methylene blue demonstrated the same in the 750-nm band, and gold nanoparticle showed the same in the 700-nm band. However, in the case of superparamagnetic iron oxide, we observed not reaction within the wavelength bands used herein to obtain imaging. Moreover, we applied selective filtering to the acquired PAT imaging to remove noise from around and reinforce the object’s area. Consequentially, we could see the object area in the imaging was effectively detected and the image noise was removed.

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