Literature DB >> 19644211

NPS characterization and evaluation of a cone beam CT breast imaging system.

Ricardo Betancourt Benítez1, Ruola Ning, David Conover, Shaohua Liu.   

Abstract

The Noise Power Spectrum (NPS) is a function that yields information about the spatial frequency composition of noise in images obtained by a system. It is evaluated by calculating the absolute value squared of the noise image and normalizing it with respect to the voxel and matrix sizes. Consequently, the NPS has been one of the physical characteristics that is commonly used to quantitatively measure the physical performance of a system. In this article, we evaluated the NPS of a Cone Beam CT Breast Imaging system by considering the following factors. First, we evaluated its symmetry around the x- and y-axis along with the influence of the cone angle and the matrix size on the NPS. Then, an analytical curve was suggested to best represent the NPS. Second, we analyzed the influence on the NPS of a set of seven parameters, namely the pixel size, exposure level, kVp value, number of projections acquired, voxel size, back projection filter, and the reconstruction algorithm employed. In addition, since the breast induced scattering in the image, we investigated the effect of the scattering-correction algorithm used in this system. Finally, we evaluated the uniformity of the NPS as a function of z with the matrix center located at {r = 0 mm}. The results demonstrate that the proposed curve is an ideal candidate that best represents the NPS. Hence, two parameters, the amplitude (A) and the width (sigma), can be used to characterize the curve. The results also demonstrate that the voxel size and the cone angle are the only two parameters investigated in this study that do not affect the NPS. On the other hand, the matrix and pixel sizes, the back-projection filter and the reconstruction algorithm, the exposure level and the scattering correction, all influence the NPS. Finally, the results of the last part of this investigation suggest that this imaging system does not have a 3D isotropic noise distribution along the z-axis; yielding less noisy images at around z = 0.00 m and z = 80 mm.

Mesh:

Year:  2009        PMID: 19644211     DOI: 10.3233/XST-2009-0213

Source DB:  PubMed          Journal:  J Xray Sci Technol        ISSN: 0895-3996            Impact factor:   1.535


  11 in total

1.  Dosimetric characterization of a dedicated breast computed tomography clinical prototype.

Authors:  Ioannis Sechopoulos; Steve Si Jia Feng; Carl J D'Orsi
Journal:  Med Phys       Date:  2010-08       Impact factor: 4.071

2.  Characterization of the homogeneous tissue mixture approximation in breast imaging dosimetry.

Authors:  Ioannis Sechopoulos; Kristina Bliznakova; Xulei Qin; Baowei Fei; Steve Si Jia Feng
Journal:  Med Phys       Date:  2012-08       Impact factor: 4.071

3.  Cupping artifact correction and automated classification for high-resolution dedicated breast CT images.

Authors:  Xiaofeng Yang; Shengyong Wu; Ioannis Sechopoulos; Baowei Fei
Journal:  Med Phys       Date:  2012-10       Impact factor: 4.071

4.  Enhancement of breast calcification visualization and detection using a modified PG method in Cone Beam Breast CT.

Authors:  Jiangkun Liu; Ruola Ning; Weixing Cai; Ricardo Betancourt Benitez
Journal:  J Xray Sci Technol       Date:  2012       Impact factor: 1.535

5.  Dose reduction with adaptive bolus chasing computed tomography angiography.

Authors:  Zhijun Cai; Er-Wei Bai; Ge Wang; Melhem J Sharafuddin; Hicham T Abada
Journal:  J Xray Sci Technol       Date:  2010       Impact factor: 1.535

6.  Dedicated breast CT: fibroglandular volume measurements in a diagnostic population.

Authors:  Srinivasan Vedantham; Linxi Shi; Andrew Karellas; Avice M O'Connell
Journal:  Med Phys       Date:  2012-12       Impact factor: 4.071

7.  Noise Power Characteristics of a Micro-Computed Tomography System.

Authors:  Muhammad U Ghani; Liqiang Ren; Molly Wong; Yuhua Li; Bin Zheng; Xiujiang John Rong; Kai Yang; Hong Liu
Journal:  J Comput Assist Tomogr       Date:  2017-01       Impact factor: 1.826

8.  Personalized estimates of radiation dose from dedicated breast CT in a diagnostic population and comparison with diagnostic mammography.

Authors:  Srinivasan Vedantham; Linxi Shi; Andrew Karellas; Avice M O'Connell; David L Conover
Journal:  Phys Med Biol       Date:  2013-10-29       Impact factor: 3.609

9.  Power spectrum analysis of the x-ray scatter signal in mammography and breast tomosynthesis projections.

Authors:  Ioannis Sechopoulos; Kristina Bliznakova; Baowei Fei
Journal:  Med Phys       Date:  2013-10       Impact factor: 4.071

10.  Sparse-view, short-scan, dedicated cone-beam breast computed tomography: image quality assessment.

Authors:  Hsin Wu Tseng; Andrew Karellas; Srinivasan Vedantham
Journal:  Biomed Phys Eng Express       Date:  2020-09-28
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