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A mobile medical QR-code authentication system and its automatic FICE image evaluation application
ARTICLE

, National Chin-Yi University of Technology, Taiwan ; , Chang Bing Show Chwan Memorial Hospital, Taiwan ; , IRCAD-Taiwan, Taiwan ; , National Chin-Yi University of Technology, Taiwan ; , IRCAD-France, France ; , ChungYung Christian University, Taiwan ; , National Chin-Yi University of Technology, Taiwan ; , National Cheng Keng University, Taiwan

Journal of Applied Research and Technology Volume 13, Number 2, ISSN 1665-6423 Publisher: Elsevier Ltd

Abstract

This paper presents an adaptive imaging technique run on a mobile service system for endoscopic image enhancement by using color transform and Gray Level Co-occurrence Matrices (GLCM) for a single input endoscopy image. The method is simply deal with the color image channels combination which chose the maximum scalar values of red, green and blue channel images, respectively. The GLCM subsequently applied for selecting the highest contrast and entropy images of the expanding image series. The enhanced endoscopy image is generated by fusing of the color, contrast and entropy images. We also proposed a service system with medical image retrieval application via quick response code authentication based on the Android operating system, which helps clinicians convenient in using mobile phone and reviewing images of the patient with cost efficiency. For the mobile technologies are growing rapidly, the mobile service system is installed to connect a Picture Archive and Communication Systems (PACS) system in hospital and applied for automatic evaluation of colon images screening. The experimental results show the proposed system is efficient for observing gastrointestinal tract polyp. The performance is evaluated and compared with Fujinon intelligent chromo endoscopy enhanced method.

Citation

Chang, Y.Y., Yan, S.L., Lin, P.Z., Zhong, H.B., Marescaux, J., Su, J.L., Wang, M.L. & Lee, P.Y. (2015). A mobile medical QR-code authentication system and its automatic FICE image evaluation application. Journal of Applied Research and Technology, 13(2), 220-229. Elsevier Ltd. Retrieved April 8, 2020 from .

This record was imported from Journal of Applied Research and Technology on January 29, 2019. Journal of Applied Research and Technology is a publication of Elsevier.

Full text is availabe on Science Direct: http://dx.doi.org/10.1016/j.jart.2015.06.020

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