Wyniki wyszukiwania - BazTech

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Internet service for wound area measurement using digital planimetry with adaptive calibration and image segmentation with deep convolutional neural networks

Foltynski Piotr, Ladyzynski Piotr

Biocybernetics and Biomedical Engineering

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2023

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Vol. 43, no. 1

17--29

EN

Uncontrolled diabetes leads to serious complications comparable to cancer. Infected foot ulcer causes a 5-year mortality of 50%. Proper treatment of foot wounds is essential, and wound area monitoring plays an important role in this area. In this article, we describe an automatic wound area measurement service that facilitates area measurement and the measurement result is based on adaptive calibration for larger accuracy at curved surfaces. Users need to take a digital picture of a wound and calibration markers and send them for analysis using an Internet page. The deep learning model based on convolutional neural networks (CNNs) was trained using 565 wound images and was used for image segmentation to identify the wound and calibration markers. The developed software calculates the wound area based on the number of pixels in the wound region and the calibration coefficient determined from distances between ticks at calibration markers. The result of the measurement is sent back to the user at the provided e-mail address. The median relative error of wound area measurement in the wound models was 1.21%. The efficacy of the CNN model was tested on 41 wounds and 73 wound models. The averaged values for the dice similarity coefficient, intersection over union, accuracy and specificity for wound identification were 90.9%, 83.9%, 99.3% and 99.6%, respectively. The service proved its high efficacy and can be used in wound area monitoring. The service may be used not only by health care specialists but also by patients. Thus, it is important tool for wound healing monitoring.

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Plantar temperature and vibration perception in patients with diabetes: A cross-sectional study

Ashok Bhargavi Haripriya, Karnam Anantha Sunitha, Janarthan Kumar

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 4

1600--1610

EN

Diabetes mellitus has many microvascular and macrovascular complications. Diabetic foot is a major consequence of these complications. Foot ulcers are the leading cause of non-traumatic amputations and early diagnosis can prevent amputation. In this study, thermal foot images and biothesiometer values of 50 control subjects and 50 known diabetic subjects were analyzed. The thermal images were analyzed using a graphical interface-enabled program developed indigenously to identify possible hotspots (abnormal temperature variation). Data comparison was conducted based on the concept of asymmetry. Temperature and vibration perception values obtained at the same points on the left and the right feet were compared. The use of a combination of thermal images and vibration perception resulted in lower incidence of false positive results in the pre-evaluation of possible plantar lesions. Pearson's correlation test was performed to analyze the statistical significance of these factors. This study concluded that the classification of factors leading to pre-ulcerative lesions in the diabetic foot could be accomplished with a higher level of confidence by using multiparameter data rather than a single-variable predictive model.

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Cukrzyca - choroba cywilizacyjna XXI wieku. Opatrunki polimerowe w leczeniu zespołu stopy cukrzycowej

Łuźniak K.

Eliksir

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2015

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nr 2

28--31