THESIS
2021
1 online resource (ix, 111 pages) : illustrations (chiefly color)
Abstract
Cancer is one of the biggest threats to human health in our lifetime. The disease affects millions of people worldwide, leaving no one unaffected. In recent years, significant progress has been made in developing new screening and treatment methods, leading to the early discovery of cancer. Detection at an early stage creates a possibility to remove the cancerous tumor via surgery. However, a major problem occurring during cancer surgery is the massive number of patients having more than one surgery due to positive margins after tumor removal. The underlying reason is the unsatisfactory gold standard method that is currently used to conduct intraoperative margin assessment. It is time-consuming due to lengthy preparation procedures and generates inaccurate results. To tackle this issue,...[
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Cancer is one of the biggest threats to human health in our lifetime. The disease affects millions of people worldwide, leaving no one unaffected. In recent years, significant progress has been made in developing new screening and treatment methods, leading to the early discovery of cancer. Detection at an early stage creates a possibility to remove the cancerous tumor via surgery. However, a major problem occurring during cancer surgery is the massive number of patients having more than one surgery due to positive margins after tumor removal. The underlying reason is the unsatisfactory gold standard method that is currently used to conduct intraoperative margin assessment. It is time-consuming due to lengthy preparation procedures and generates inaccurate results. To tackle this issue, PhoMedics are in the process of commercializing a cutting-edge imaging technology coined CHAMP - Computational High-throughput Autofluorescence Microscopy with Pattern Illumination, which has the potential to revolutionize the standard of care. PhoMedics solution is a combination of hardware and software. The hardware generates high-resolution subcellular images of the tissue cells which are then virtually stained using our deep-learning software, imitating the golden standard images that medical professionals are used to interpreting. CHAMP can complete the whole procedure within a few minutes and the images are seamlessly sent to a pathologist for instant diagnosis. Such technology can help eliminate the need of second surgeries, thus saving tons of clinical resources for the healthcare system and easing the physical and mental burden among cancer patients. This thesis explains how such a revolutionizing technology can be taken to the market and commercialized.
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