LesionAir : a low-cost tool for automated skin cancer diagnosis and mapping
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.
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| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2016
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| Online Access: | http://hdl.handle.net/1721.1/104499 |
| _version_ | 1811092997615386624 |
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| author | Wortman, Tyler David |
| author2 | Alexander H. Slocum. |
| author_facet | Alexander H. Slocum. Wortman, Tyler David |
| author_sort | Wortman, Tyler David |
| collection | MIT |
| description | Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016. |
| first_indexed | 2024-09-23T15:37:56Z |
| format | Thesis |
| id | mit-1721.1/104499 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T15:37:56Z |
| publishDate | 2016 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1044992019-04-12T16:21:11Z LesionAir : a low-cost tool for automated skin cancer diagnosis and mapping Low-cost tool for automated skin cancer diagnosis and mapping Wortman, Tyler David Alexander H. Slocum. Massachusetts Institute of Technology. Department of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering. Mechanical Engineering. Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016. Cataloged from PDF version of thesis. Includes bibliographical references (pages 235-252). Skin cancer is the most common form of cancer in the United States; one out of every five Americans develops skin cancer at some point in their lifetime. Diagnosing cancerous lesions early is critical as it significantly increases the chance of survival. However, current techniques for diagnosing skin cancer lack specificity and sensitivity, resulting in many unnecessary biopsies and missed diagnoses. Although some researchers have increased diagnostic efficacy by quantitatively diagnosing skin cancer in an automated fashion, these methods require extremely bulky, expensive, and complicated equipment. This thesis presents the design and testing of LesionAir, a small, low-cost skin cancer diagnostic tool that measures the full-field compliance of the skin - which is well known to correlate strongly with skin cancer - by applying a vacuum force to the tissue and measuring precise deflection using structured light 3D reconstruction. Image processing algorithms determine additional morphological information about the potentially cancerous lesion. A pilot study of ten patients with suspect lesions validated LesionAir's effectiveness. 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 stiffened tissue aligned nearly perfectly with the bounds established by the histological tests, which showed the method determines the precise coordinates that must be excised to safely remove all cancerous tissue. This technology can thus enable patients, primary care physicians, and dermatologists to rapidly identify and diagnose skin cancer with diagnostic quality not seen before from any equipment in this class. by Tyler David Wortman. Ph. D. 2016-09-30T19:32:20Z 2016-09-30T19:32:20Z 2016 2016 Thesis http://hdl.handle.net/1721.1/104499 958278365 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 252 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Mechanical Engineering. Wortman, Tyler David LesionAir : a low-cost tool for automated skin cancer diagnosis and mapping |
| title | LesionAir : a low-cost tool for automated skin cancer diagnosis and mapping |
| title_full | LesionAir : a low-cost tool for automated skin cancer diagnosis and mapping |
| title_fullStr | LesionAir : a low-cost tool for automated skin cancer diagnosis and mapping |
| title_full_unstemmed | LesionAir : a low-cost tool for automated skin cancer diagnosis and mapping |
| title_short | LesionAir : a low-cost tool for automated skin cancer diagnosis and mapping |
| title_sort | lesionair a low cost tool for automated skin cancer diagnosis and mapping |
| topic | Mechanical Engineering. |
| url | http://hdl.handle.net/1721.1/104499 |
| work_keys_str_mv | AT wortmantylerdavid lesionairalowcosttoolforautomatedskincancerdiagnosisandmapping AT wortmantylerdavid lowcosttoolforautomatedskincancerdiagnosisandmapping |