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在MRI中使用增强的U-Net与初始模块和双输出机制的自动腰椎细分

Jaysel Theresa Silveira1, Girisha S1, Poornima Panduranga Kundapur2

  • 1Department of Data Science and Computer Applications, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.

Scientific reports
|November 10, 2025
PubMed
概括

这项研究引入了一种增强的U-Net模型,用于精确的腰椎脊柱MRI细分. 深度学习方法改善了脊椎,脊椎间盘 (IVD) 和脊柱管道的识别,以便更好地诊断.

关键词:
二进制细分的二进制细分.双输出机制 双输出机制开始模块的开始模块.腰椎脊椎细分的细分 腰椎脊椎的细分多类细分化的多类细分化.语义细分 语义细分是指语义细分.这就是U-Net.

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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...