Zobrazeno 1 - 10
of 141
pro vyhledávání: '"Zhaoying Bian"'
Publikováno v:
IEEE Access, Vol 9, Pp 15200-15211 (2021)
Sparse-view scanning has great potential for realizing ultra-low-dose computed tomography (CT) examination. However, noise and artifacts in reconstructed images are big obstacles, which must be handled to maintain the diagnosis accuracy. Existing spa
Externí odkaz:
https://doaj.org/article/a185cf47645c41a4b23a801f95ea2297
Autor:
Jiaojiao Li, Shanzhou Niu, Jing Huang, Zhaoying Bian, Qianjin Feng, Gaohang Yu, Zhengrong Liang, Wufan Chen, Jianhua Ma
Publikováno v:
PLoS ONE, Vol 10, Iss 10, p e0140579 (2015)
Statistical iterative reconstruction (SIR) for X-ray computed tomography (CT) under the penalized weighted least-squares criteria can yield significant gains over conventional analytical reconstruction from the noisy measurement. However, due to the
Externí odkaz:
https://doaj.org/article/8ea1ec45215441049251169933996e57
Autor:
Zhaoying Bian, Jing Huang, Jianhua Ma, Lijun Lu, Shanzhou Niu, Dong Zeng, Qianjin Feng, Wufan Chen
Publikováno v:
PLoS ONE, Vol 9, Iss 2, p e89282 (2014)
Dynamic positron emission tomography (PET) imaging is a powerful tool that provides useful quantitative information on physiological and biochemical processes. However, low signal-to-noise ratio in short dynamic frames makes accurate kinetic paramete
Externí odkaz:
https://doaj.org/article/73d66c97cf56478991159c7ffeca9f32
Autor:
Jing Huang, Yunwan Zhang, Jianhua Ma, Dong Zeng, Zhaoying Bian, Shanzhou Niu, Qianjin Feng, Zhengrong Liang, Wufan Chen
Publikováno v:
PLoS ONE, Vol 8, Iss 11, p e79709 (2013)
X-ray computed tomography (CT) iterative image reconstruction from sparse-view projection data has been an important research topic for radiation reduction in clinic. In this paper, to relieve the requirement of misalignment reduction operation of th
Externí odkaz:
https://doaj.org/article/568d4b82e8a44a7c92e80f2616e12294
Publikováno v:
IEEE Transactions on Medical Imaging. 41:3849-3861
Deep learning (DL)-based methods show great potential in computed tomography (CT) imaging field. The DL-based reconstruction methods are usually evaluated on the training and testing datasets which are obtained from the same distribution, i.e., the s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b463c645ebf6aed1e16f2ac16c154435
https://doi.org/10.1109/tmi.2022.3197400
https://doi.org/10.1109/tmi.2022.3197400
Publikováno v:
Medical Imaging 2023: Physics of Medical Imaging.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::598cfc5a0f7915d1387bcfb85b822c4f
https://doi.org/10.1117/12.2654207
https://doi.org/10.1117/12.2654207
Autor:
Zerui Mao, Yongbo Wang, Gaofeng Chen, Manman Zhu, MingQiang Meng, Zhaoying Bian, Dong Zeng, Jianhua Ma
Publikováno v:
Medical Imaging 2023: Physics of Medical Imaging.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b6f84e294079e829414a0dba4815e80
https://doi.org/10.1117/12.2654204
https://doi.org/10.1117/12.2654204
Deep learning-based 'All-in-One' combined visualization strategy for disease screening in CT imaging
Autor:
Hao Zhou, Jingyi Liao, Zhixiong Zeng, Danyang Li, Yongbo Wang, Zhaoying Bian, Dong Zeng, Jianhua Ma
Publikováno v:
Medical Imaging 2023: Physics of Medical Imaging.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9ad7e9a95ead1f48660cade06b277aaa
https://doi.org/10.1117/12.2654188
https://doi.org/10.1117/12.2654188
Publikováno v:
Medical Imaging 2023: Physics of Medical Imaging.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d5376410c25e10e78d98631bb90a516
https://doi.org/10.1117/12.2654205
https://doi.org/10.1117/12.2654205
Publikováno v:
Medical Imaging 2023: Physics of Medical Imaging.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9565cac94357e781ce7f758d39b80d3
https://doi.org/10.1117/12.2654202
https://doi.org/10.1117/12.2654202