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相关概念视频

Brain Imaging01:14

Brain Imaging

247
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...
247

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Intraoperative Registration by Cross-Modal Inverse Neural Rendering.

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相关实验视频

Updated: Jul 15, 2025

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping
13:12

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

Published on: August 12, 2019

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记住:大脑切除多式成像数据库

Parikshit Juvekar1, Reuben Dorent1, Fryderyk Kögl1,2

  • 1Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

medRxiv : the preprint server for health sciences
|September 25, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了最大的脑瘤成像公共数据库,结合了MRI和手术内超声波 (iUS) 数据. 本资源旨在推进人工智能驱动的图像分析,并改进用于脑瘤切除的神经外科技术.

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Comprehensive Autopsy Program for Individuals with Multiple Sclerosis
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Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
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相关实验视频

Last Updated: Jul 15, 2025

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping
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Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

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Comprehensive Autopsy Program for Individuals with Multiple Sclerosis
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科学领域:

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

背景情况:

  • 最大安全的手术切除是脑瘤的标准,但脑部转移和难以将瘤与健康组织区分开来使手术复杂化.
  • 神经导航系统由于手术期间的大脑转移而失去准确性.
  • 术内超声波 (iUS) 和术内核磁共振 (iMRI) 有助于可视化,但iUS的组织对比度低于iMRI.

研究的目的:

  • 创建最大的公共数据库,用于手术治疗脑瘤的手术内MRI和超声数据.
  • 支持人工智能研究,用于医学图像分析,脑部转移补偿和神经外科训练.

主要方法:

  • 编制了114名连续接受脑瘤手术治疗的患者的数据集.
  • 收集了369个手术前的MRI系列,320个3DiUS系列,301个iMRI系列和356个细分.
  • 包括质瘤 (n=92),转移 (n=11) 和其他瘤类型 (n=11) 的数据.

主要成果:

  • 建立了最大的MRI和脑瘤手术的IUS公共数据库.
  • 该数据库包含来自单一机构的全面成像和细分数据.
  • 该数据集适用于开发和验证神经外科应用的AI算法.

结论:

  • 这种全面的数据库预计将有助于大脑转移校正和医学图像分析的研究.
  • 它还将支持神经外科培训,特别是解释手术中的超声波和MRI数据.
  • 促进开发和验证用于脑瘤成像的AI算法.