Advances in Machine Learning-Aided Thermal Imaging for Early Detection of Diabetic Foot Ulcers: A Review.

Journal: Biosensors
PMID: 39727879

Abstract

The prevention and early warning of foot ulcers are crucial in diabetic care; however, early microvascular lesions are difficult to detect and often diagnosed at later stages, posing serious health risks. Infrared thermal imaging, as a rapid and non-contact clinical examination technology, can sensitively detect hidden neuropathy and vascular lesions for early intervention. This review provides an informative summary of the background, mechanisms, thermal image datasets, and processing techniques used in thermal imaging for warning of diabetic foot ulcers. It specifically focuses on two-dimensional signal processing methods and the evaluation of computer-aided diagnostic methods commonly used for diabetic foot ulcers.

Authors

  • Longyan Wu
    Academy for Engineering and Technology, Fudan University, Shanghai, 200433, China.
  • Ran Huang
    Academy for Engineering and Technology, Fudan University, Shanghai, 200433, China. huangran@fudan.edu.cn.
  • Xiaoyan He
    Academy for Engineering and Technology, Yiwu Research Institute, Fudan University, Shanghai 200433, China.
  • Lisheng Tang
    Academy for Engineering and Technology, Yiwu Research Institute, Fudan University, Shanghai 200433, China.
  • Xin Ma
    Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.

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