| dc.contributor.author | Carlson, Jay D. | |
| dc.contributor.author | Perez, Edward | |
| dc.contributor.author | Wortman, Tyler D. | |
| dc.contributor.author | Slocum Jr., Alexander H | |
| dc.date.accessioned | 2019-03-22T14:34:57Z | |
| dc.date.available | 2019-03-22T14:34:57Z | |
| dc.date.issued | 2018-03 | |
| dc.date.submitted | 2018-01 | |
| dc.identifier.issn | 1932-6181 | |
| dc.identifier.uri | http://hdl.handle.net/1721.1/121052 | |
| dc.description.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 0.085mm 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.sponsorship | National Science Foundation (U.S.) (Grant 1122374) | en_US |
| dc.publisher | ASME International | en_US |
| dc.relation.isversionof | http://dx.doi.org/10.1115/1.4039209 | en_US |
| dc.rights | Article 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.source | ASME | en_US |
| dc.title | LesionAir: An Automated, Low-Cost Vision-Based Skin Cancer Diagnostic Tool | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Wortman, 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 ASME | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Mechanical Engineering | en_US |
| dc.contributor.mitauthor | Wortman, Tyler D. | |
| dc.contributor.mitauthor | Slocum Jr., Alexander H | |
| dc.relation.journal | Journal of Medical Devices | en_US |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dc.date.updated | 2019-01-02T19:18:26Z | |
| dspace.orderedauthors | Wortman, Tyler D.; Carlson, Jay D.; Perez, Edward; Slocum, Alexander H. | en_US |
| dspace.embargo.terms | N | en_US |
| dc.identifier.orcid | https://orcid.org/0000-0002-6803-3787 | |
| mit.license | PUBLISHER_POLICY | en_US |