A deep unrolling network based on cartoon texture decomposition for low-dose CT reconstruction

Tingyue Liu, Zhiguo Gui, Yi Liu, Jinxin Luo, Zhen Sun, Pengcheng Zhang

Open source

DOI: 10.1088/1361-6560/aea2ec
Published: 2026-09-21
Container: Physics in Medicine & Biology
Publisher: IOP Publishing
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1088/1361-6560/aea2ec,
  title = {A deep unrolling network based on cartoon texture decomposition for low-dose CT reconstruction},
  author = {Tingyue Liu and Zhiguo Gui and Yi Liu and Jinxin Luo and Zhen Sun and Pengcheng Zhang},
  year = {2026},
  journal = {Physics in Medicine \&amp; Biology},
  doi = {10.1088/1361-6560/aea2ec},
  url = {https://doi.org/10.1088/1361-6560/aea2ec}
}

RIS

TY  - JOUR
TI  - A deep unrolling network based on cartoon texture decomposition for low-dose CT reconstruction
AU  - Tingyue Liu
AU  - Zhiguo Gui
AU  - Yi Liu
AU  - Jinxin Luo
AU  - Zhen Sun
AU  - Pengcheng Zhang
PY  - 2026
JO  - Physics in Medicine &amp; Biology
DO  - 10.1088/1361-6560/aea2ec
UR  - https://doi.org/10.1088/1361-6560/aea2ec
ER  -

APA

Liu, T., Gui, Z., Liu, Y., Luo, J., Sun, Z., & Zhang, P. (2026). A deep unrolling network based on cartoon texture decomposition for low-dose CT reconstruction. Physics in Medicine & Biology. https://doi.org/10.1088/1361-6560/aea2ec

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crossref · retrieved 2026-09-25T18:10:14.064Z