Intelligent medical assistant: AI medical image assistance technology and its application in cancer diagnosis and treatment decision

Yuli He

doi:10.1117/12.3049255

17 October 2024 Intelligent medical assistant: AI medical image assistance technology and its application in cancer diagnosis and treatment decision

Yuli He

Author Affiliations +

Proceedings Volume 13289, International Conference on Optical Communication and Optoelectronic Technology (OCOT 2024); 132890M (2024) https://doi.org/10.1117/12.3049255
Event: The International Conference on Optical Communication and Optoelectronic Technology (OCOT 2024), 2024, Hangzhou, China

Abstract

Artificial intelligence (AI) is a computer technology that has a human way of thinking and can imitate the human brain. The integration of AI into medical imaging has revolutionized diagnosis and treatment, providing significant advances in diagnostic accuracy, treatment planning, and patient care. In the context of widespread global cancer challenges, this study will focus on the effectiveness of AI technology for early detection in the field of imaging and histological image analysis, and review strategies for using image processing technology to detect tumors. We discussed the latest AIdriven technologies, including deep learning algorithms, computer-aided detection systems (CAD), and computer-aided diagnosis (CADx), which excel at processing large data sets to produce accurate and valid results in cancer detection, helping imaging physicians accurately identify cancer, and enhancing early cancer diagnosis. And then improve the patient's prognosis through therapeutic intervention.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuli He "Intelligent medical assistant: AI medical image assistance technology and its application in cancer diagnosis and treatment decision", Proc. SPIE 13289, International Conference on Optical Communication and Optoelectronic Technology (OCOT 2024), 132890M (17 October 2024); https://doi.org/10.1117/12.3049255

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