Discriminative Feature Representation to Improve Projection Data Inconsistency for Low Dose CT Imaging-Reference-Cited by-同舟云学术

Discriminative Feature Representation to Improve Projection Data Inconsistency for Low Dose CT Imaging

Published:2017-12 Issue:12 Volume:36 Page:2499-2509
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Liu Jin,Ma Jianhua^ORCID,Zhang Yi^ORCID,Chen Yang^ORCID,Yang Jian^ORCID,Shu Huazhong,Luo Limin,Coatrieux Gouenou,Yang Wei^ORCID,Feng Qianjin,Chen Wufan

Funder

State’s Key Project of Research and Development Plan

National Natural Science Foundation

Fundamental Research Funds for the Central Universities

Qing Lan Project in Jiangsu Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software

Link

http://xplorestaging.ieee.org/ielx7/42/8124116/08010446.pdf?arnumber=8010446

Cited by 102 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Adaptive noise-aware denoising network: Effective denoising for CT images with varying noise intensity;Biomedical Signal Processing and Control;2024-10

2. Generation model meets swin transformer for unsupervised low-dose CT reconstruction;Machine Learning: Science and Technology;2024-04-04

3. Machine Learning and Computer Vision Based Methods for Cancer Classification: A Systematic Review;Archives of Computational Methods in Engineering;2024-02-12

4. Non-sample fuzzy based convolutional neural network model for noise artifact in biomedical images;Discover Applied Sciences;2024-01-20

5. Low-Dose CT Image Synthesis for Domain Adaptation Imaging Using a Generative Adversarial Network With Noise Encoding Transfer Learning;IEEE Transactions on Medical Imaging;2023-09