Adaptive nonlocal means-regularized iterative image reconstruction for sparse-view CT

Hao Zhang, Jianhua Ma, Jing Wang, Yan Liu, Hao Han, William Moore, Michael Salerno, Zhengrong Liang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Low-dose X-ray computed tomography (CT) imaging is desirable for various clinical applications due to the growing concerns about excessive radiation exposure to the patients. One strategy to achieve low-dose CT imaging is to lower the number of projection views per rotation during data acquisition. However, the resulting image by the conventional filtered back-projection method may suffer from view-aliasing artifacts due to insufficient angular sampling. In this work, we propose a nonlocal means (NLM)-regularized iterative reconstruction scheme for low-dose CT from sparse-view acquisitions. In order to improve the quality of reconstructed images, we further introduce spatial adaptivity to the NLM-based regularization by considering the local characteristics of images. The resulting approach is termed as adaptive NLM-regularized iterative image reconstruction. Experimental results demonstrated the feasibility of the presented reconstruction scheme for sparse-view CT and the superiority of incorporating the spatial adaptivity.

Original languageEnglish (US)
Title of host publication2014 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479960972
DOIs
StatePublished - Mar 10 2016
EventIEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014 - Seattle, United States
Duration: Nov 8 2014Nov 15 2014

Other

OtherIEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014
CountryUnited States
CitySeattle
Period11/8/1411/15/14

Fingerprint

Computer-Assisted Image Processing
image reconstruction
tomography
Tomography
dosage
X Ray Computed Tomography
projection
Artifacts
radiation dosage
data acquisition
artifacts
acquisition
sampling
x rays

ASJC Scopus subject areas

  • Nuclear and High Energy Physics
  • Radiology Nuclear Medicine and imaging

Cite this

Zhang, H., Ma, J., Wang, J., Liu, Y., Han, H., Moore, W., ... Liang, Z. (2016). Adaptive nonlocal means-regularized iterative image reconstruction for sparse-view CT. In 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014 [7430948] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NSSMIC.2014.7430948

Adaptive nonlocal means-regularized iterative image reconstruction for sparse-view CT. / Zhang, Hao; Ma, Jianhua; Wang, Jing; Liu, Yan; Han, Hao; Moore, William; Salerno, Michael; Liang, Zhengrong.

2014 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014. Institute of Electrical and Electronics Engineers Inc., 2016. 7430948.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhang, H, Ma, J, Wang, J, Liu, Y, Han, H, Moore, W, Salerno, M & Liang, Z 2016, Adaptive nonlocal means-regularized iterative image reconstruction for sparse-view CT. in 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014., 7430948, Institute of Electrical and Electronics Engineers Inc., IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014, Seattle, United States, 11/8/14. https://doi.org/10.1109/NSSMIC.2014.7430948
Zhang H, Ma J, Wang J, Liu Y, Han H, Moore W et al. Adaptive nonlocal means-regularized iterative image reconstruction for sparse-view CT. In 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014. Institute of Electrical and Electronics Engineers Inc. 2016. 7430948 https://doi.org/10.1109/NSSMIC.2014.7430948
Zhang, Hao ; Ma, Jianhua ; Wang, Jing ; Liu, Yan ; Han, Hao ; Moore, William ; Salerno, Michael ; Liang, Zhengrong. / Adaptive nonlocal means-regularized iterative image reconstruction for sparse-view CT. 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014. Institute of Electrical and Electronics Engineers Inc., 2016.
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