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contributor authorWortman, Tyler D.
contributor authorCarlson, Jay D.
contributor authorPerez, Edward
contributor authorSlocum, Alexander H.
date accessioned2019-02-28T11:05:00Z
date available2019-02-28T11:05:00Z
date copyright3/5/2018 12:00:00 AM
date issued2018
identifier issn1932-6181
identifier othermed_012_02_021001.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4252489
description abstractCurrent techniques for diagnosing skin cancer lack specificity and sensitivity, resulting in unnecessary biopsies and missed diagnoses. Automating tissue palpation and morphology quantification will result in a repeatable, objective process. LesionAir is a low-cost skin cancer diagnostic tool that measures the full-field compliance of tissue by applying a vacuum force and measuring the precise deflection using structured light three-dimensional (3D) reconstruction. The technology was tested in a benchtop setting on phantom skin and in a small clinical study. LesionAir has been shown to measure deflection with a 0.085 mm root-mean-square (RMS) error and measured the stiffness of phantom tissue to within 20% of finite element analysis (FEA) predictions. After biopsy and analysis, a dermatopathologist confirmed the diagnosis of skin cancer in tissue that LesionAir identified as noticeably stiffer and the regions of this stiffer tissue aligned with the bounds of the lesion. A longitudinal, full-scale study is required to determine the clinical efficacy of the device. This technology shows initial promise as a low-cost tool that could rapidly identify and diagnose skin cancer.
publisherThe American Society of Mechanical Engineers (ASME)
titleLesionAir: An Automated, Low-Cost Vision-Based Skin Cancer Diagnostic Tool
typeJournal Paper
journal volume12
journal issue2
journal titleJournal of Medical Devices
identifier doi10.1115/1.4039209
journal fristpage21001
journal lastpage021001-6
treeJournal of Medical Devices:;2018:;volume( 012 ):;issue: 002
contenttypeFulltext


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