人工智能在影像医学中的实际应用

程齐; 欧阳雪晖

doi:10.12122/j.issn.1674-4500.2023.03.34

人工智能在影像医学中的实际应用

doi: 10.12122/j.issn.1674-4500.2023.03.34

程齐^1,,
欧阳雪晖^2, ,

1.
内蒙古医科大学内蒙古临床医学院，内蒙古呼和浩特 010110
2.
内蒙古自治区人民医院影像医学科，内蒙古呼和浩特 010017

详细信息

作者简介:
程齐，在读硕士研究生，E-mail: 945621245@qq.com

通讯作者:
欧阳雪晖，主任技师，教授，E-mail: 18748324400@139.com

计量
- 文章访问数: 424
- HTML全文浏览量: 271
- PDF下载量: 55
- 被引次数: 0
出版历程
- 收稿日期: 2023-03-13
- 网络出版日期: 2023-06-15
- 刊出日期: 2023-05-20

Practical application of artificial intelligence in imaging medicine

CHENG Qi^1
,,
OUYANG Xuehui^{2
, ,}

1.
Inner Mongolia Clinical Medical College, Inner Mongolia Medical University, Hohhot 010110, China
2.
Department of Imaging Medicine Inner Mongolia Autonomous Region People's Hospital, Hohhot 010017, China

摘要

摘要: 在医疗领域影像医学是人工智能的主要应用方向之一。在日常诊疗工作中，影像检查的临床需求量巨大，但影像科医师数量的增长和临床经验的积累远不及影像数据的增长速度，AI与影像数据交叉融合，可减轻影像科医师处理海量影像数据的压力。目前，基于超声、X线、CT和MRI数据以深度学习技术为核心，已研发了多种AI辅助影像的定量分析算法，在临床得到广泛的应用，实现了疾病的早期诊断、精准治疗、疗效评估和预测，显著提高影像科医师处理影像信息的效率和准确性，可为临床诊疗提供定量依据。
- 人工智能 /
- 深度学习 /
- 影像医学 /
- 临床应用
Abstract: Imaging medicine is one of the main application directions of artificial intelligence in the medical field. In daily diagnosis and treatment work, the clinical demand for imaging examination is huge, but the growth of the number of imaging physicians and the accumulation of clinical experience is far from the growth rate of imaging data. The cross fusion of artificial intelligence and imaging data can reduce the pressure of imaging physicians to process massive image data. At present, based on deep learning technology and ultrasound, X-ray, CT and MRI data, various artificial intelligence assisted imaging quantitative analysis algorithms have been developed and widely applied in clinical practice, achieving early diagnosis, precise treatment, efficacy evaluation, and prediction of diseases, significantly improving the efficiency and accuracy of imaging physicians in processing image information, and providing quantitative basis for clinical diagnosis and treatment.
- artificial intelligence /
- deep learning /
- imaging medicine /
- clinical application

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