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相关概念视频

Computed Tomography01:10

Computed Tomography

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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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State Space Representation01:27

State Space Representation

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The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
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相关实验视频

Updated: Jun 14, 2025

Visualization of Low-Level Gamma Radiation Sources Using a Low-Cost, High-Sensitivity, Omnidirectional Compton Camera
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Published on: January 30, 2020

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一个新的视觉状态空间模型用于低剂量CT无噪声.

Jiexing Huang1, Anni Zhong2, Yajing Wei3

  • 1Department of Radiation Oncology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.

Medical physics
|September 4, 2024
PubMed
概括

一个新的Visual Mamba编码解码网络 (ViMEDnet) 有效地拒绝低剂量计算机断层扫描 (LDCT) 图像. 该模型有效地捕捉了本地和全球特征,优于现有的CNN和变压器方法,提高了诊断质量.

关键词:
马姆巴·马姆巴是什么意思国家空间模型国家空间模型拒绝的意思是拒绝.低剂量CTCT的使用.

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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

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相关实验视频

Last Updated: Jun 14, 2025

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科学领域:

  • 医疗成像医学成像
  • 人工智能的人工智能
  • 图像处理 图像处理

背景情况:

  • 低剂量计算机断层扫描 (LDCT) 减少了辐射暴露,但受到影响临床实用性的噪音和文物的影响.
  • 卷积神经网络 (CNN) 和变压器对于LDCT的否定是常见的,但在建模能力或计算复杂性方面存在局限性.

研究的目的:

  • 开发一个简单,高效的LDCT denoising模型,具有线性计算复杂性.
  • 该模型旨在有效地捕捉当地空间环境和远程依赖关系.

主要方法:

  • 介绍Visual Mamba编码解码网络 (ViMEDnet),将国家空间模型应用于LDCT的报销.
  • 建议混合状态空间模块 (MSSM) 结合深度卷,最大共享和2D选择性扫描模块 (2DSSM) 进行本地和全球特征提取.
  • 使用加权梯度敏感混合损失函数,在无声化过程中保存图像细节.

主要成果:

  • 与五种最先进的方法相比,ViMEDnet表现出卓越的视觉质量和定量性能.
  • 该模型有效地消除了噪音和文物,同时保留了精细的结构和低对比度的边缘.
  • 定量指标显示,ViMEDnet获得了最低的RMSE和最高的PSNR,SSIM和FSIM分数.

结论:

  • ViMEDnet为最不发达国家和地区 (LDCT) 宣传提供了卓越的性能.
  • 它为现有的CNN和基于变压器的无线化模型提供了一个可行的替代方案.