LesionAir: An Automated, Low-Cost Vision-Based Skin Cancer Diagnostic Tool
| Autor: | Edward Perez, Jay D. Carlson, Tyler D. Wortman, Alexander H. Slocum |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Vision based
business.industry Biomedical Engineering Medicine (miscellaneous) Stiffness Structural engineering medicine.disease Finite element method 3. Good health 030207 dermatology & venereal diseases 03 medical and health sciences 0302 clinical medicine Deflection (engineering) 030220 oncology & carcinogenesis medicine medicine.symptom Skin cancer business |
| Zdroj: | Journal of Medical Devices. 12 |
| ISSN: | 1932-619X 1932-6181 |
| DOI: | 10.1115/1.4039209 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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