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相关概念视频

Brain Imaging01:14

Brain Imaging

229
Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
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Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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肝脏成像中的人工智能:方法和应用.

Peng Zhang1, Chaofei Gao1, Yifei Huang2

  • 1Institute for TCM-X, MOE Key Laboratory of Bioinformatics, Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University, Beijing, China.

Hepatology international
|February 20, 2024
PubMed
概括
此摘要是机器生成的。

人工智能 (AI) 正通过先进的医学成像分析,彻底改变肝病管理. 人工智能提高了精确的检测,诊断和治疗,影响了肝脏护理的未来.

关键词:
人工智能的人工智能是人工智能.深度学习是一种深度学习.肝脏疾病是一种肝脏疾病.医学成像医学成像多式联运数据多式联运数据

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科学领域:

  • 放射学 放射学是一门学科.
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 肝脏疾病是全球健康面临的重大挑战.
  • 准确的诊断和治疗肝病非常重要.
  • 医学成像在肝脏疾病管理中起着至关重要的作用.

研究的目的:

  • 审查目前在肝脏成像中的人工智能 (AI) 方法.
  • 探索AI在肝脏疾病的检测,诊断和治疗中的应用.
  • 讨论人工智能在肝脏成像中的挑战和未来方向.

主要方法:

  • 专注于用于肝脏成像的深度学习方法.
  • 总结代表性的人工智能技术.
  • 举例说明整个肝病谱的临床应用.

主要成果:

  • 人工智能在复杂的医学图像特征的定量评估方面表现出色.
  • 人工智能在改善临床医生对医学图像的定性解释方面表现有前途.
  • 人工智能应用包括精确的肝病检测,诊断和治疗.

结论:

  • 人工智能方法,结合大型医疗图像数据集,准备改变肝病护理.
  • 未来发展的关键领域包括特征解释性,多式联运数据集成和多中心研究.
  • 人工智能具有显著的潜力,可以影响未来的肝脏疾病管理.