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    LesionAir: An Automated, Low-Cost Vision-Based Skin Cancer Diagnostic Tool

    Source: Journal of Medical Devices:;2018:;volume( 012 ):;issue: 002::page 21001
    Author:
    Wortman, Tyler D.
    ,
    Carlson, Jay D.
    ,
    Perez, Edward
    ,
    Slocum, Alexander H.
    DOI: 10.1115/1.4039209
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Current 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.
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      LesionAir: An Automated, Low-Cost Vision-Based Skin Cancer Diagnostic Tool

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4252489
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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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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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