Researchers develop deep-learning technique to ID at-risk anatomy in CT scans

Radiation therapy is one of the most widely used cancer treatments, but a drawback of the procedure is that it can cause collateral damage to healthy tissue in proximity to cancerous growths. Identifying organs at risk via CT scans is a difficult and labor-intensive process, but UCI computer scientists and researchers from other institutions have developed an automated technique to perform this function using a deep-learning algorithm. Their work was published recently in Nature Machine Intelligence.

from News on Artificial Intelligence and Machine Learning https://ift.tt/2oJLLFN

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