A comparison study of sinogram- and image-domain penalized re-weighted least-squares approaches to noise reduction for low-dose cone-beam CT

Hao Zhang, Yan Liu, Hao Han, Jing Wang, Jianhua Ma, Lihong Li, Zhengrong Liang

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

3 Scopus citations

Abstract

Reducing X-ray exposure to the patients is one of the major research efforts in the computed tomography (CT) field, and one of the common strategies to achieve it is to lower the mAs setting (by lowering the X-ray tube current and/or shortening the exposure time) in currently available CT scanners. However, the image quality from low mAs acquisition is severely degraded due to excessive quantum noise, if no adequate noise control is applied during image reconstruction. Different from filter-based algorithms, statistical reconstruction algorithms model the statistical property of the noise using a cost function and minimize the cost function for an optimal solution in statistical sense. The algorithms have shown to be feasible and effective in both sinogram and image domain. In our previous researches, we proposed penalized reweighted least-squares (PRWLS) approaches to sinogram noise reduction and image reconstruction for low-dose CT imaging, which are in this statistical category. This work is a continuation of the research along this direction and aims to compare the reconstruction quality of two different PRWLS implementations for low-dose cone-beam CT reconstruction: (1) PRWLS sinogram restoration followed by analytical Feldkamp-Davis- Kress reconstruction, (2) fully iterative PRWLS image reconstruction. Inspired by our recent study on the variance of low-mAs projection data in presence of electric noise background, a more accurate weight was adopted in the weighted least-squares term. An anisotropic quadratic form penalty was utilized in both PRWLS implementations to preserve edges during noise reduction. Experiments using the CatPhan® 600 phantom and anthropomorphic head phantom were carried to study the relevant performance of these two implementations on image reconstruction. The results revealed that the implementation (2) can outperform implementation (1) in terms of noise-resolution tradeoff measurement and analysis of the reconstructed small objects due to its matched image edge-preserved penalty in the image domain. However, those gains are offset by the cost of increased computational time. Thus, further examination of real patient data is necessary to show the clinical significance of the iterative PRWLS image reconstruction over the PRWLS sinogram restoration.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2013
Subtitle of host publicationPhysics of Medical Imaging
DOIs
StatePublished - Jun 3 2013
EventMedical Imaging 2013: Physics of Medical Imaging - Lake Buena Vista, FL, United States
Duration: Feb 11 2013Feb 14 2013

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume8668
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2013: Physics of Medical Imaging
CountryUnited States
CityLake Buena Vista, FL
Period2/11/132/14/13

Keywords

  • Low-dose cone-beam CT
  • Noise reduction
  • Noise-resolution tradeoff
  • Penalized re-weighted least-squares

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

Fingerprint Dive into the research topics of 'A comparison study of sinogram- and image-domain penalized re-weighted least-squares approaches to noise reduction for low-dose cone-beam CT'. Together they form a unique fingerprint.

  • Cite this

    Zhang, H., Liu, Y., Han, H., Wang, J., Ma, J., Li, L., & Liang, Z. (2013). A comparison study of sinogram- and image-domain penalized re-weighted least-squares approaches to noise reduction for low-dose cone-beam CT. In Medical Imaging 2013: Physics of Medical Imaging [86683E] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 8668). https://doi.org/10.1117/12.2007111