Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques.

ABSTRACT: Diabetes mellitus (DM) can lead to plantar ulcers, amputation and death. Plantar foot thermogram images acquired using an infrared camera have been shown to detect changes in temperature distribution associated with a higher risk of foot ulceration. Machine learning approaches applied to such infrared images may have utility in the early diagnosis of diabetic foot complications. In this work, a publicly available dataset was categorized into different classes, which were corroborated by domain experts, based on a temperature distribution parameter-the thermal change index (TCI). We then explored different machine-learning approaches for classifying thermograms of the TCI-labeled dataset. Classical machine learning algorithms with feature engineering and the convolutional neural network (CN

SUBMITTER: Khandakar A 

PROVIDER: S-EPMC8915003 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature