Poster + Paper
20 June 2024 AI-enabled smart LSCI system for early diagnosis of diabetic foot ulcers
Aqeel Ur-Rehman, Sadia Noureen, Humberto Cabrera, Hafiz Saad Khaliq, Muhammad Qasim Mehmood, Muhammad Zubair
Author Affiliations +
Conference Poster
Abstract
Diabetic foot ulcers (DFU) are open sores or wounds that develop on the feet of people with diabetes. They are a serious complication and often occur on the bottom of the foot. DFU treatment in the field of medical sciences is an advanced field of study. Patients with DFU have a five-year death rate of approximately 40%. Age, gender, medical history, vascular diseases, and renal illness are major risk factors for mortality. While 90% of people with diabetes worldwide have type 2 diabetes mellitus, accounting for 463 million cases of the disease. DFU diagnosis and treatment has been performed with Laser Speckle Contrast Imaging (LSCI) which is a non-invasive imaging technology. LSCI is becoming widely recognized as a vital technique for evaluating the impacts and implications of this disease. Major types of LSCI has been studied for the application of laser speckle technology in medical diagnosis. Region of Interest (ROI) and Multi exposure based LSCI applications and implementations has been reviewed in this study. Along with the application of conventional LSCI, Artificial Intelligence (AI) tools has been studied for robust results to combat issues associated with diabetes.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Aqeel Ur-Rehman, Sadia Noureen, Humberto Cabrera, Hafiz Saad Khaliq, Muhammad Qasim Mehmood, and Muhammad Zubair "AI-enabled smart LSCI system for early diagnosis of diabetic foot ulcers", Proc. SPIE 13006, Biomedical Spectroscopy, Microscopy, and Imaging III, 130061L (20 June 2024); https://doi.org/10.1117/12.3022044
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KEYWORDS
Laser speckle contrast imaging

Artificial intelligence

Blood circulation

Tissues

Biomedical optics

Diabetic foot ulcers

Biomedical applications

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