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相关概念视频

Imaging Studies IV: Magnetic Resonance Imaging01:27

Imaging Studies IV: Magnetic Resonance Imaging

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Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...
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Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

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Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
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Brain Imaging01:14

Brain Imaging

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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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相关实验视频

Updated: Jan 9, 2026

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
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前列腺MRI中的人工智能:通过新兴技术解决当前的局限性

Patricia M Johnson1,2,3, Lavanya Umapathy1,2, Bradley Gigax4

  • 1Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.

Journal of magnetic resonance imaging : JMRI
|December 5, 2025
PubMed
概括
此摘要是机器生成的。

人工智能 (AI) 可以增强前列腺MRI,以更早地检测和管理前列腺癌. 人工智能解决方案正在改善图像采集,质量和解释,使前列腺MRI更可靠和可扩展.

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.前列腺核磁共振 (MRI) 的前列腺.

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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:

  • 前列腺MRI对于前列腺癌检测和风险分层至关重要.
  • 目前的局限性包括高成本,解释变化和可扩展性问题.
  • 假阴性,假阳性和长时间的获取影响了可靠性和吞吐量.

研究的目的:

  • 审查人工智能 (AI) 在前列腺MRI中的进展和应用.
  • 综合人工智能在五个关键领域的进展:分拣,获取,质量保证,诊断和预后.
  • 要突出人工智能在前列腺MRI中的证据水平,验证状态和采用障碍.

主要方法:

  • 文献综述综合了前列腺MRI人工智能方面的进展.
  • 分析人工智能在患者分拣,加速获取/重建,质量保证,病变检测和预后建模中的应用.
  • 证据水平的评估,验证和临床采用障碍.

主要成果:

  • 人工智能在完善患者分拣和通过深度学习重建加速MRI获取方面显示出重大潜力.
  • 用于病变检测和癌症预测的AI模型显示性能与放射学家相美.
  • 虽然获取和重建工具是先进的 (FDA-cleared),但分拣,质量控制和预后应用程序处于早期的开发阶段.

结论:

  • 人工智能提供解决方案,以提高前列腺MRI的可靠性,可扩展性和效率.
  • 需要进一步的研究和前性试验,以确保公平的表现,并将AI纳入常规临床实践.
  • 人工智能有可能将前列腺MRI转化为人口层面前列腺癌管理的可扩展平台.