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Breast cancer is a leading cause of female cancer deaths, but early detection significantly reduces mortality rates. Annual mammograms are common for women aged 40 and older, but those under 40 often go undiagnosed. False negatives are a concern, especially with dense breast tissue. Many women with detected lesions or genetic risk experience stress during follow-up and have difficulty with self-examinations. Limited access to reliable diagnostic systems increases undetected cancer risk, influenced by ethnicity and socio-economic factors.
We propose a portable, rapid, non-invasive, low-cost, and user-friendly tool for early-stage breast cancer detection. This device helps women familiarize themselves with their breasts. Specialists can also use it for screening and follow-up. The device uses a red-light source to illuminate the breast, with malignant tumors absorbing light and appearing as dark shadows. A mounted camera captures images, which are analyzed using image analysis and deep learning. This semi-automatic approach sends images and analysis to physicians for further evaluation. The App allows for additional services and features over time.
Commercializing such a device poses significant challenges. Medical assistive devices carry high commercial risks, and the business model is complex. The highly competitive medical device market requires extensive market research and thorough data collection, analysis, and integration before manufacturing. This project allows for the development of a business model, focusing on legal procedures and standards for medical device development. Additionally, it involves gathering and analyzing market research data to assess the feasibility and success of commercialization, aiming to find a safe path to market.
Vivian Mushahwar
Edmonton Unlimited
Engineering
Professional, scientific and technical services; Public administration
University of Alberta
Business Strategy Internship
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