Literature DB >> 29121540

Computer aided diagnosis of diabetic foot using infrared thermography: A review.

Muhammad Adam1, Eddie Y K Ng2, Jen Hong Tan3, Marabelle L Heng4, Jasper W K Tong5, U Rajendra Acharya6.   

Abstract

Diabetes mellitus (DM) is a chronic metabolic disorder that requires regular medical care to prevent severe complications. The elevated blood glucose level affects the eyes, blood vessels, nerves, heart, and kidneys after the onset. The affected blood vessels (usually due to atherosclerosis) may lead to insufficient blood circulation particularly in the lower extremities and nerve damage (neuropathy), which can result in serious foot complications. Hence, an early detection and treatment can prevent foot complications such as ulcerations and amputations. Clinicians often assess the diabetic foot for sensory deficits with clinical tools, and the resulting foot severity is often manually evaluated. The infrared thermography is a fast, nonintrusive and non-contact method which allows the visualization of foot plantar temperature distribution. Several studies have proposed infrared thermography-based computer aided diagnosis (CAD) methods for diabetic foot. Among them, the asymmetric temperature analysis method is more superior, as it is easy to implement, and yielded satisfactory results in most of the studies. In this paper, the diabetic foot, its pathophysiology, conventional assessments methods, infrared thermography and the different infrared thermography-based CAD analysis methods are reviewed.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Atherosclerosis; Diabetes; Foot; Infrared image; Neuropathy; Plantar

Mesh:

Year:  2017        PMID: 29121540     DOI: 10.1016/j.compbiomed.2017.10.030

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  9 in total

1.  Lipohypertrophic Skin Changes in Patients With Diabetes: Visualization by Infrared Images.

Authors:  Lars Kaltheuner; Matthias Kaltheuner; Lutz Heinemann
Journal:  J Diabetes Sci Technol       Date:  2018-06-01

2.  Thermography as a non-ionizing quantitative tool for diagnosing periapical inflammatory lesions.

Authors:  Christoph Bourauel; Sameh Talaat; M Atef Aboushady; Wael Talaat; Zaid Hamdoon; Tarek M Elshazly; Nivin Ragy
Journal:  BMC Oral Health       Date:  2021-05-13       Impact factor: 2.757

3.  Automated Detection of Infection in Diabetic Foot Ulcer Images Using Convolutional Neural Network.

Authors:  J Yogapriya; Venkatesan Chandran; M G Sumithra; B Elakkiya; A Shamila Ebenezer; C Suresh Gnana Dhas
Journal:  J Healthc Eng       Date:  2022-04-06       Impact factor: 2.682

4.  The difference in heat transport characteristics of the heart and lung meridians: A comparative study of COPD patients and healthy subjects.

Authors:  Xiaoyu Li; Yongliang Jiang; Hantong Hu; Yajun Zhang; Jiali Lou; Xiaofen He; Jing Sun; Yuanyuan Wu; Junfan Fang; Xiaomei Shao; Jianqiao Fang
Journal:  Medicine (Baltimore)       Date:  2021-02-05       Impact factor: 1.817

5.  Thermal Analysis of Blood Flow Alterations in Human Hand and Foot Based on Vascular-Porous Media Model.

Authors:  Yue-Ping Wang; Rui-Hao Cheng; Ying He; Li-Zhong Mu
Journal:  Front Bioeng Biotechnol       Date:  2022-01-28

6.  Use of infrared thermography in medical diagnostics: a scoping review protocol.

Authors:  Dorothea Kesztyüs; Sabrina Brucher; Tibor Kesztyüs
Journal:  BMJ Open       Date:  2022-04-01       Impact factor: 2.692

7.  Infrared thermal imaging-based skin temperature response during cupping at two different negative pressures.

Authors:  Xulong Liu; Yanli Wang; Zhenying Wu
Journal:  Sci Rep       Date:  2022-09-15       Impact factor: 4.996

8.  Differential Screening of Herniated Lumbar Discs Based on Bag of Visual Words Image Classification Using Digital Infrared Thermographic Images.

Authors:  Gi Nam Kim; Ho Yeol Zhang; Yong Eun Cho; Seung Jun Ryu
Journal:  Healthcare (Basel)       Date:  2022-06-13

9.  Deep Learning Classification for Diabetic Foot Thermograms.

Authors:  Israel Cruz-Vega; Daniel Hernandez-Contreras; Hayde Peregrina-Barreto; Jose de Jesus Rangel-Magdaleno; Juan Manuel Ramirez-Cortes
Journal:  Sensors (Basel)       Date:  2020-03-22       Impact factor: 3.576

  9 in total

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