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相关概念视频

Brain Imaging01:14

Brain Imaging

264
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...
264

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Updated: Jul 26, 2025

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence
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使用人工智能技术进行脑瘤检测和查:当前趋势和未来前景.

U Raghavendra1, Anjan Gudigar1, Aritra Paul1

  • 1Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India.

Computers in biology and medicine
|June 17, 2023
PubMed
概括

早期发现脑瘤对于有效治疗至关重要. 本综述强调了人工智能 (AI) 和计算机辅助诊断 (CAD) 系统如何帮助识别脑瘤,讨论当前的挑战和未来的研究方向.

关键词:
大脑瘤是什么?这就是为什么CTCTCTCTCTCT分类 分类 分类 分类.深度学习是一种深度学习.这就是为什么MRI是MRI.机器学习 机器学习在这里,PET是PET.分段化 分段化 分段化 分段化

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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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Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
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科学领域:

  • 神经学 神经学
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 大脑瘤是头骨内的异常生长,可以导致严重的健康问题并增加死亡率,特别是恶性类型.
  • 早期发现脑瘤对于及时干预和改善患者结果至关重要.
  • 计算机辅助诊断 (CAD) 系统与人工智能 (AI) 集成,在早期识别脑瘤方面显示出重大前景.

研究的目的:

  • 审查关于用于脑瘤检测的计算机辅助诊断 (CAD) 系统的现有文献.
  • 在各种成像模式中识别与当前CAD系统相关的挑战和局限性.
  • 概述当前对人工智能驱动的大脑瘤诊断的要求和未来研究前景.

主要方法:

  • 对2000年至2022年间发表的124篇研究文章进行系统审查.
  • 基于不同医学成像模式的CAD系统面临的挑战的分析.
  • 识别人工智能领域的当前需求和未来趋势,用于脑瘤检测.

主要成果:

  • 该审查确定了用于脑瘤检测的CAD系统的关键挑战,包括数据可变性,算法概括性和可解释性.
  • 不同的成像模式为基于AI的分析带来了独特的挑战.
  • 越来越需要强大可靠的AI工具来支持临床医生在早期脑瘤诊断.

结论:

  • 人工智能和CAD系统是早期发现脑瘤的重要工具,有可能提高诊断的准确性和速度.
  • 应对已确定的挑战对于这些技术的进步和临床采用至关重要.
  • 未来的研究应该专注于开发更复杂的AI算法,多式联络数据集成和临床验证,以提高脑瘤诊断和患者护理.