RESEARCH ARTICLE
An Integrated Hardware and Software Application to Support Wound Measurement Using a 3D Scanner and Image Processing Techniques
Kriangkrai Tassanavipas1, *, Suriya Natsupakpong1
Article Information
Identifiers and Pagination:
Year: 2020Volume: 14
First Page: 55
Last Page: 73
Publisher ID: TOBEJ-14-55
DOI: 10.2174/1874120702014010055
Article History:
Received Date: 12/05/2020Revision Received Date: 06/09/2020
Acceptance Date: 30/09/2020
Electronic publication date: 21/12/2020
Collection year: 2020
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Aim:
To build wounds volume(3D) and area(2D) measuring system and device.
Background:
The measurement of the wound depth has been troublesome due to difficulty fo the procedures, physicians mostly avoid inspecting the wound depth as it could cause wound inflammation and infection.
Objective:
To build a contactless device for measuring wound volume and develop the system to support the wound treatment process which offers precise measurement and wound healing progression.
Methods:
Build a machine to control and stabilize 3D-scanner over the wound using a servo motor and apply the image processing technique to calculate the wound's area and volume. Comparing the machine accuracy by using Archimedes's principle testing with various wound model sizes, made from folding clay and pork rinds.
Results:
The device and system generate an error value of less than 15% which is within a satisfactory level.
Conclusion:
Knowing the wound depth is vital for the treatment, direct contact to the wound area can cause inflammation, infection, and increase time to heal. This device will help physicians to get more insight into the wound and improve the treatment plan for the patients.
There are certain limitations to be considered for future work. Firstly, different software components used in the image processing and estimation process could be integrated to enhance user experience. Secondly, it is possible to apply Machine Learning techniques to identify the wounded area on the wound image file.
