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Automated detection of spinal tumor utilizing deep learning based on object detection from MRI Sadayuki Ito 1 1Department of Orthopedic Surgery Nagoya University Graduate School of Medicine Keyword: 人工知能 , 脊椎疾患 , 画像診断 pp.787-792
Published Date 2024/11/10
DOI https://doi.org/10.18888/rp.0000002786
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This article discusses the application of artificial intelligence(AI)in spinal and spinal cord diseases, particularly focusing on image diagnosis. AI technologies, such as machine learning and deep learning, are rapidly advancing and improving diagnostic accuracy in detecting conditions like spinal tumors, fractures, and scoliosis. This article highlights the development of AI models for automatic labeling, tumor classification, and Cobb angle estimation. It also addresses challenges such as data quality, the need for explainable AI, and ethical concerns, while emphasizing the potential of AI to enhance diagnostic precision and optimize treatment planning in spinal surgery.


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電子版ISSN 印刷版ISSN 0009-9252 金原出版

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