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3 October 2022 Colorectal cancer detection on portable devices using deep learning (Conference Presentation)
Raef Taha
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Proceedings Volume PC12225, Optics and Photonics for Information Processing XVI; PC1222509 (2022) https://doi.org/10.1117/12.2640402
Event: SPIE Optical Engineering + Applications, 2022, San Diego, California, United States
Abstract
Colorectal cancer is a very common cancer and is currently the second most common cause of death from cancer. It is a very serious cancer, and receiving proper treatment is critical. Testing for microsatellite instability (MSI), which is present in 15% of colorectal cancer cases, is currently an expensive and very time-consuming process. However, testing is necessary for these individuals, to help determine how their treatment should progress. This paper presents a deep learning algorithm to distinguish between MSI and MSS scans. It shows that by heavily compressing these types of algorithms, they can run on embedded computing systems such as a raspberry pi or a cell phone. These computing systems can be cheap and use little power. The algorithms can still retain relatively high accuracy, in this case around 80%. Colorectal deep learning algorithms have not been implemented on low power devices in prior publications.
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Raef Taha "Colorectal cancer detection on portable devices using deep learning (Conference Presentation)", Proc. SPIE PC12225, Optics and Photonics for Information Processing XVI, PC1222509 (3 October 2022); https://doi.org/10.1117/12.2640402
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KEYWORDS
Colorectal cancer
Cancer
Evolutionary algorithms
Multispectral imaging
Computing systems
Algorithm development
Pathology
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