• Laser & Optoelectronics Progress
  • Vol. 58, Issue 8, 0800002 (2021)
Mingzhu Zhao1, Yan Zhang1、2、*, and Yingyan Zhu1
Author Affiliations
  • 1College of Big Data and Information Engineering, Guizhou University, Guiyang,Guizhou 550025, China
  • 2Research Center of Nondestructive Testing for Agricultural Products, Guiyang University, Guiyang, Guizhou 550005,China
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    DOI: 10.3788/LOP202158.0800002 Cite this Article Set citation alerts
    Mingzhu Zhao, Yan Zhang, Yingyan Zhu. Research Progress of Early Disease Detection Technology Based on Infrared Thermography[J]. Laser & Optoelectronics Progress, 2021, 58(8): 0800002 Copy Citation Text show less
    Workflow of infrared thermal imaging detection system
    Fig. 1. Workflow of infrared thermal imaging detection system
    Infrared thermograms of breast masses[6]. (a)Patient with invasive ductal carcinoma; (b)patient with fibroadenoma; (c)patient with cyst
    Fig. 2. Infrared thermograms of breast masses[6]. (a)Patient with invasive ductal carcinoma; (b)patient with fibroadenoma; (c)patient with cyst
    Skin cancer detection algorithm block diagram
    Fig. 3. Skin cancer detection algorithm block diagram
    Comparison of infrared thermograms of hands in patients with carpal tunnel syndrome[12].(a)Before operation; (b)after operation;(c)healthy volunteer
    Fig. 4. Comparison of infrared thermograms of hands in patients with carpal tunnel syndrome[12].(a)Before operation; (b)after operation;(c)healthy volunteer
    Process of myocardial ischemic pre-diagnosis based on infrared imaging data[21]
    Fig. 5. Process of myocardial ischemic pre-diagnosis based on infrared imaging data[21]
    Infrared thermograms of face.(a)Patient with left-sided peripheral facial paralysis;(b)patient with central facial paralysis;(c)healthy volunteer
    Fig. 6. Infrared thermograms of face.(a)Patient with left-sided peripheral facial paralysis;(b)patient with central facial paralysis;(c)healthy volunteer
    Basic structure diagram of convolutional neural network
    Fig. 7. Basic structure diagram of convolutional neural network
    ItemPathological examinationAccuracy/%Sensitivity/%Specificity/%
    MalignantBenign
    Mammography
    Malignant591996.180.897.6
    Benign14761
    Color Doppler ultrasonography
    Malignant632695.886.396.6
    Benign10754
    Far-infrared thermography
    Malignant661797.190.497.8
    Benign7763
    Table 1. Comparison of mammography, ultrasonography, and far-infrared thermography in the diagnosis of breast lesions less than 2 cm in diameter (n=853)[18]
    ItemPathological examinationAccuracy/%Sensitivity/%Specificity/%
    MalignantBenign
    Mammography
    Malignant35411685.084.985.1
    Benign63660
    Color Doppler ultrasonography
    Malignant3967891.795.090.0
    Benign21698
    Far-infrared thermography
    Malignant3753993.290.095.0
    Benign42737
    Table 2. Comparison of mammography, ultrasonography, and far-infrared thermography in the diagnosis of breast lesions large than 2 cm in diameter (n=1193)[18]
    ItemAccuracy/%Sensitivity/%Specificity/%
    Original images
    CNN62.823.9100
    Differential thermal images
    CNN73.497.865.2
    AdaBoost87.291.383.3
    Table 3. Comparison of breast cancer classification results based on differential thermal images
    Mingzhu Zhao, Yan Zhang, Yingyan Zhu. Research Progress of Early Disease Detection Technology Based on Infrared Thermography[J]. Laser & Optoelectronics Progress, 2021, 58(8): 0800002
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