Literature DB >> 28718523

Error rate of automated calculation for wound surface area using a digital photography.

S Yang1, J Park2, H Lee2, J B Lee3, B U Lee2, B H Oh3.   

Abstract

BACKGROUND: Although measuring would size using digital photography is a quick and simple method to evaluate the skin wound, the possible compatibility of it has not been fully validated.
PURPOSE: To investigate the error rate of our newly developed wound surface area calculation using digital photography.
METHODS: Using a smartphone and a digital single lens reflex (DSLR) camera, four photographs of various sized wounds (diameter: 0.5-3.5 cm) were taken from the facial skin model in company with color patches. The quantitative values of wound areas were automatically calculated. The relative error (RE) of this method with regard to wound sizes and types of camera was analyzed.
RESULTS: RE of individual calculated area was from 0.0329% (DSLR, diameter 1.0 cm) to 23.7166% (smartphone, diameter 2.0 cm). In spite of the correction of lens curvature, smartphone has significantly higher error rate than DSLR camera (3.9431±2.9772 vs 8.1303±4.8236). However, in cases of wound diameter below than 3 cm, REs of average values of four photographs were below than 5%. In addition, there was no difference in the average value of wound area taken by smartphone and DSLR camera in those cases.
CONCLUSION: For the follow-up of small skin defect (diameter: <3 cm), our newly developed automated wound area calculation method is able to be applied to the plenty of photographs, and the average values of them are a relatively useful index of wound healing with acceptable error rate.
© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  image analysis; photography; smartphone; wounds and Injuries

Mesh:

Year:  2017        PMID: 28718523     DOI: 10.1111/srt.12398

Source DB:  PubMed          Journal:  Skin Res Technol        ISSN: 0909-752X            Impact factor:   2.365


  1 in total

1.  Wound area measurement with 3D transformation and smartphone images.

Authors:  Chunhui Liu; Xingyu Fan; Zhizhi Guo; Zhongjun Mo; Eric I-Chao Chang; Yan Xu
Journal:  BMC Bioinformatics       Date:  2019-12-18       Impact factor: 3.169

  1 in total

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