Measuring Surface Area of Skin Lesions with 2D and 3D Algorithms

Abstract

Purpose The treatment of skin lesions of various kinds is a common task in clinical routine. Apart from wound care, the assessment of treatment efficacy plays an important role. In this paper, we present a new approach to measure the skin lesion surface in two and three dimensions. Methods For the 2D approach, a single photo containing a flexible paper ruler is taken. After semi-automatic segmentation of the lesion, evaluation is based on local scale estimation using the ruler. For the 3D approach, reconstruction is based on Structure from Motion. Roughly outlining the region of interest around the lesion is required for both methods. Results The measurement evaluation was performed on 117 phantom images and five phantom videos for 2D and 3D approach, respectively. We found an absolute error of 0.99±1.18 cm2 and a relative error 9.89± 9.31% for 2D. These errors are <1 cm2 and <5% for five test phantoms in our 3D case. As expected, the error of 2D surface area measurement increased by approximately 10% for wounds on the bent surface compared to wounds on the flat surface. Using our method, the only user interaction is to roughly outline the region of interest around the lesion. Conclusions We developed a new wound segmentation and surface area measurement technique for skin lesions even on a bent surface. The 2D technique provides the user with a fast, user-friendly segmentation and measurement tool with reasonable accuracy for home care assessment of treatment. For 3D only preliminary results could be provided. Measurements were only based on phantoms and have to be repeated with real clinical data.

Digital Planimetry With a New Adaptive Calibration Procedure Results in Accurate and Precise Wound Area Measurement at Curved Surfaces

“…24 Other authors had a small sample size based on which the error was estimated. 16,17 In the studies presented in the Introduction section, the average error of area measurement was about 5% ± 1%, and it was larger than the mean error obtained in this study for the DPwAC of 0.70% (Table 1). Mean of RDs, which is a measure of systematic error, should be zero for an unbiased measurement method.…”

“…Other authors used similar cylinder diameters to simulate a curved surface, for example, 8.8 cm for the Silhouette device' 24 or 9.0 cm in or the MolecuLight i:X device. 12 Gentler surface curvatures were used in Mirzaalian-Dastjerdi et al 17 with cylinder diameters of 17 and 39 cm.…”

“…The accuracy of their system in area measurement was 95%. Mirzaalian-Dastjerdi et al 17 showed a 3D wound measurement system based on the video taken from different angles showing a wound to be measured and a calibration ruler. They reported a mean relative error (RE) of their system of 4.22% ± 0.45% on phantom images.…”

Translation of Pharmacodynamic Biomarkers of Antibiotic Efficacy in Specific Populations to Optimize Doses

“…Refinement of this outcome measure is specifically addressed in current guidance by moving beyond the multiplication of length and width for surface area [ 23 ]. Imaging technologies exist to translate photos of the lesion and convert them to surface area measurements that in theory could be performed on a daily or twice daily basis to capture time-course data [ 36 ]. Building an exposure–response relationship on this regulatory accepted clinical endpoint would in theory allow for improved granularity of differences in outcomes in specific populations.…”

Convolution Neural Network with Coordinate Attention for Real-Time Wound Segmentation and Automatic Wound Assessment

“…These factors make large-scale wound care extremely difficult in emergency situations [1]. Meanwhile, body surface wounds, such as scratches and burns, can lead to infection and poor blood circulation if not treated in time or amputation in severe cases [2][3][4]. Generally, the area and depth of the wound are manually estimated by medical staff [5].…”