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Nonradiative infrared thermography detection based on artificial intelligence analysis replaces traditional CT detection

  • Jiaqi Chen
  • , Xin Su*
  • , Jingyi Gong*
  • , Ruihan Hu*
  • *Corresponding author for this work
  • Institute of Intelligent Manufacturing, Guangdong Academy of Sciences
  • Ltd
  • Ltd.
  • National Pilot School of Software, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

CT examination utilizes computational functions to achieve tomography of the human body based on the basic characteristics of X-rays, thereby unavoidably producing ionizing radiation that can cause damage to the human body. So, it is not applicable to pregnant women and children; Repeated exposure to CT irradiation in a short period of time may cause leukocytosis, fatigue, dizziness, vomiting and other symptoms. In particular, pregnant women, neonates and patients with extreme weakness are more likely to develop malformation, cancers and other adverse effects after exposure to radiation. However, endoscopic examination will induce physical damage to a certain extent, leading to potential risks of inflammation, and its process will cause fear and discomfort to patients, among which children are more likely to show fear than adults. In addition, there are many practical operation problems for endoscopic examination. So, it is not an ideal method. The medical infrared thermal imaging instrument adopts the high-tech infrared detection technology, which has no radiation and does not touch the human body. When the human body is diseased, the heat balance of the diseased part will also be destroyed. The infrared thermal imaging captures this imbalance based on the infrared rays from the human body to form an infrared thermogram, which reflects the temperature characteristics of the human body and thus will not harm the human body. The instrument has now already passed the clinical verification. Infrared thermography can well reflect the presentation of sinusitis, especially performs well in distinguishing whether the inflammation is acute or chronic. And the expression on infrared thermography is better than CT. Combined with artificial intelligence imaging algorithms, it can achieve feature analysis at the level of a single pixel and provide doctors with more detailed and accurate reference data, so as to implement efficient auxiliary diagnosis. The instrument is suitable for various types of hospitals and medical institutions, and even for home medical diagnosis when it is combined with a remote auxiliary diagnosis system.

Original languageEnglish
Title of host publicationThird International Seminar on Artificial Intelligence, Networking, and Information Technology, AINIT 2022
EditorsNaijing Hu, Guanglin Zhang
PublisherSPIE
ISBN (Electronic)9781510662964
DOIs
StatePublished - 2023
Externally publishedYes
Event3rd International Seminar on Artificial Intelligence, Networking, and Information Technology, AINIT 2022 - Shanghai, China
Duration: 23 Sep 202225 Sep 2022

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12587
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference3rd International Seminar on Artificial Intelligence, Networking, and Information Technology, AINIT 2022
Country/TerritoryChina
CityShanghai
Period23/09/2225/09/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • artificial intelligence
  • infrared clinical diagnosis
  • nonradiative infrared thermography

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