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Real-time noise reduction based on ground truth free deep learning for optical coherence tomography
YONG HUANG
*
, NAN ZHANG,
QUN HAO
*
此作品的通讯作者
光电学院
Beijing Institute of Technology
科研成果
:
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同行评审
34
引用 （Scopus）
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探究 'Real-time noise reduction based on ground truth free deep learning for optical coherence tomography' 的科研主题。它们共同构成独一无二的指纹。
分类
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按字母排序
Engineering
Deep Learning
100%
Ground Truth
100%
Signal-to-Noise Ratio
75%
Demonstrates
50%
Computation Time
50%
Averaging Method
50%
Edge Preservation
50%
Limitations
25%
Imaging Systems
25%
High Resolution
25%
Image Processing
25%
Noise Ratio
25%
Averaging Technique
25%
Acquisition Time
25%
Graphics Processing Unit
25%
Imaging Modality
25%
Computer Science
Deep Learning
100%
super resolution
100%
Residual Neural Network
100%
Noise-to-Signal Ratio
37%
Computation Time
25%
Edge Preservation
25%
de-noising
12%
Imaging Systems
12%
Network Structures
12%
Image Processing
12%
Image Quality
12%
Training Model
12%
3D Imaging
12%
Graphics Processing Unit
12%
Acquisition Time
12%
Image Acquisition
12%
Imaging Modality
12%
Earth and Planetary Sciences
Real Time
100%
Tomography
100%
Noise Reduction
100%
Signal to Noise Ratios
42%
High Resolution
14%
Image Processing
14%
Material Science
Optical Coherence Tomography
100%
Signal-to-Noise Ratio
42%