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Updated: May 14, 2026

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
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Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

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基于U-Net的深度学习框架的审查,用于基于MRI的脑瘤分割.

Ayse Bastug Koc1,2, Devrim Akgun3

  • 1Computer and Informatics Engineering Department, Institute of Natural Science and Technology, Sakarya University, Esentepe Campus, 54050 Serdivan, Sakarya, Türkiye.

Diagnostics (Basel, Switzerland)
|February 27, 2026
PubMed
概括

这篇评论分析了35项基于U-Net的脑瘤细分研究,使用MRI扫描. 它详细介绍了U-Net架构的进步及其在临床应用中的有效性.

关键词:
在BRATS数据集中,这就是U-Net.在U-Net的变体中.大脑瘤的细分 脑瘤的细分瘤子区域 瘤子区域

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Imaging Studies IV: Magnetic Resonance Imaging

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,...