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dc.contributor.authorCarlson, Jay D.
dc.contributor.authorPerez, Edward
dc.contributor.authorWortman, Tyler D.
dc.contributor.authorSlocum Jr., Alexander H
dc.date.accessioned2019-03-22T14:34:57Z
dc.date.available2019-03-22T14:34:57Z
dc.date.issued2018-03
dc.date.submitted2018-01
dc.identifier.issn1932-6181
dc.identifier.urihttp://hdl.handle.net/1721.1/121052
dc.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 0.085mm 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.en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant 1122374)en_US
dc.publisherASME Internationalen_US
dc.relation.isversionofhttp://dx.doi.org/10.1115/1.4039209en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceASMEen_US
dc.titleLesionAir: An Automated, Low-Cost Vision-Based Skin Cancer Diagnostic Toolen_US
dc.typeArticleen_US
dc.identifier.citationWortman, Tyler D., Jay D. Carlson, Edward Perez, and Alexander H. Slocum. “LesionAir: An Automated, Low-Cost Vision-Based Skin Cancer Diagnostic Tool.” Journal of Medical Devices 12, no. 2 (March 5, 2018): 021001. © 2018 by ASMEen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.contributor.mitauthorWortman, Tyler D.
dc.contributor.mitauthorSlocum Jr., Alexander H
dc.relation.journalJournal of Medical Devicesen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2019-01-02T19:18:26Z
dspace.orderedauthorsWortman, Tyler D.; Carlson, Jay D.; Perez, Edward; Slocum, Alexander H.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-6803-3787
mit.licensePUBLISHER_POLICYen_US


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