MM-Net: Multiframe and Multimask-Based Unsupervised Deep Denoising for Low-Dose Computed Tomography-Reference-Cited by-同舟云学术

MM-Net: Multiframe and Multimask-Based Unsupervised Deep Denoising for Low-Dose Computed Tomography

Published:2023-03 Issue:3 Volume:7 Page:296-306
ISSN:2469-7311
Container-title:IEEE Transactions on Radiation and Plasma Medical Sciences
language:
Short-container-title:IEEE Trans. Radiat. Plasma Med. Sci.

Author:

Jeon Sun-Young¹^ORCID,Kim Wonjin¹^ORCID,Choi Jang-Hwan¹^ORCID

Affiliation:

1. Division of Mechanical and Biomedical Engineering, Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul, South Korea

Funder

Korea Medical Device Development Fund

Technology Development Program of MSS

National Research Foundation of Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Radiology, Nuclear Medicine and imaging,Instrumentation,Atomic and Molecular Physics, and Optics

Link

http://xplorestaging.ieee.org/ielx7/7433213/10058049/09963593.pdf?arnumber=9963593

Reference77 articles.

1. Low-dose 4DCT reconstruction via temporal nonlocal means

2. Unsupervised Training of Denoisers for Low-Dose CT Reconstruction Without Full-Dose Ground Truth

3. A Review of Image Denoising Algorithms, with a New One

4. Noise2Inverse: Self-Supervised Deep Convolutional Denoising for Tomography

5. Spectral CT Reconstruction With Image Sparsity and Spectral Mean

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