切片间互补性增强了使用中央区域增强神经网络去除环形工件的功能

相关实验视频

Updated: Jan 16, 2026

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

1.0K

Yikun Zhang1,2, Guannan Liu1,2, Zhanghao Chen1,2

  • 1Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, Nanjing 210096, People's Republic of China.

Physics in medicine and biology
|September 30, 2025
PubMed
概括

由于复杂的探测器反应,光子计数探测器计算机断层扫描 (CT) 系统面临环形工件. 新的切片间互补性增强环物件去除 (ICE-RAR) 算法有效地减少这些物件,提高图像质量.

关键词:
中央地区加强神经网络计算机断层扫描 (CT) 是一种计算机断层扫描.深度学习是一种深度学习.切片之间的互补性.戒指工件 移除 删除 删除

更多相关视频

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography04:48

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

Published on: November 30, 2022

3.3K
Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility07:46

Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility

Published on: August 9, 2024

1.2K

相关概念视频

Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
693