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Volume 42 Issue 11
Nov.  2020
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GAO Yubao, JIANG Tao, HU Xiaocheng, JIANG Qiong, YANG Changchun, LIU Zeliang, QI Shikai. Method of High Precision Medical Infrared Thermography[J]. Infrared Technology , 2020, 42(11): 1111-1118.
Citation: GAO Yubao, JIANG Tao, HU Xiaocheng, JIANG Qiong, YANG Changchun, LIU Zeliang, QI Shikai. Method of High Precision Medical Infrared Thermography[J]. Infrared Technology , 2020, 42(11): 1111-1118.
shu

Method of High Precision Medical Infrared Thermography

  • 1.

    School of Electronic Engineering, Jiujiang University, Jiujiang 332005, China

  • 2.

    Jiangxi medical college of Nanchang University, Nanchang 330031, China

  • 3.

    Department of Gynecology, The Affiliated Jiujiang Hospital of Nanchang University, Jiujiang 332000, China

  • 4.

    Department of Neonatology, Jiujiang Maternal and Child Care Centres, Jiujiang 332000, China

  • 5.

    School of Information Science and Technology, Jiujiang University, Jiujiang 332005, China

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  • Received Date: June 06, 2020
  • Revised Date: November 08, 2020
    Graphical Abstract
    • Abstract
  • It is difficult to directly distinguish the human body area identified by the infrared data measured by medical infrared thermal imaging equipment from the temperature data obtained by conversion. It is often necessary to convert it into image data and use image processing technology to obtain the region of interest and the biological characteristics from the temperature data in the given area. Accordingly, disease screening or diagnosis can be realized. However, conversion from 14-bit infrared data to 8-bit image data incurs a serious loss of data accuracy, resulting in poor processing performance. In this paper, a new expression method for thermal images is proposed. The obtained color thermal image contains the original precision temperature data information and the color enhancement effect under the setting scale of the temperature observation window. At the same time, it contains the temperature data record and the setting rules of the observation window. Through the inverse transformation of the image data, the original temperature data can be reproduced and the color enhancement effect can be changed. The thermal image provided by this method can be used in different infrared thermal image systems without requiring additional access to temperature data files. This will be more aligned with the development trend of big data and artificial intelligence.
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    • References (29)
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