去模糊
深度学习
人工智能
领域(数学)
计算机断层摄影术
图像(数学)
降噪
计算机科学
机器学习
图像复原
图像处理
放射科
医学
数学
纯数学
作者
Yiming Lei,Chuang Niu,Junping Zhang,Ge Wang,Hongming Shan
出处
期刊:IEEE transactions on radiation and plasma medical sciences
[Institute of Electrical and Electronics Engineers]
日期:2023-12-12
卷期号:8 (2): 153-172
被引量:9
标识
DOI:10.1109/trpms.2023.3341903
摘要
This article reviews the deep learning methods for computed tomography image denoising and deblurring separately and simultaneously. Then, we discuss promising directions in this field, such as a combination with large-scale pretrained models and large language models. Currently, deep learning is revolutionizing medical imaging in a data-driven manner. With rapidly evolving learning paradigms, related algorithms and models are making rapid progress toward clinical applications.
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