title: Approximations of noise covariance in multi-slice helical CT scans: impact on lung nodule size estimation.
abstract: Multi-slice computed tomography (MSCT) scanners have become popular volumetric imaging tools. Deterministic and random properties of the resulting CT scans have been studied in the literature. Due to the large number of voxels in the three-dimensional (3D) volumetric dataset, full characterization of the noise covariance in MSCT scans is difficult to tackle. However, as usage of such datasets for quantitative disease diagnosis grows, so does the importance of understanding the noise properties because of their effect on the accuracy of the clinical outcome. The goal of this work is to study noise covariance in the helical MSCT volumetric dataset. We explore possible approximations to the noise covariance matrix with reduced degrees of freedom, including voxel-based variance, one-dimensional (1D) correlation, two-dimensional (2D) in-plane correlation and the noise power spectrum (NPS). We further examine the effect of various noise covariance models on the accuracy of a prewhitening matched filter nodule size estimation strategy. Our simulation results suggest that the 1D longitudinal, 2D in-plane and NPS prewhitening approaches can improve the performance of nodule size estimation algorithms. When taking into account computational costs in determining noise characterizations, the NPS model may be the most efficient approximation to the MSCT noise covariance matrix.
authors: US Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging and Applied Mathematics, 10903 New Hampshire Ave., Silver Spring, MD 20993, USA. rongping.zeng@fda.hhs.gov
authors: Rongping
authors: R
authors: Zeng
authors: Nicholas
authors: N
authors: Petrick
authors: Marios A
authors: MA
authors: Gavrielides
authors: Kyle J
authors: KJ
authors: Myers
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D019047:Phantoms, Imaging; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D059629:Signal-To-Noise Ratio; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging* / Q000473:pathology; D015898:Tomography Scanners, X-Ray Computed; D036542:Tomography, Spiral Computed / Q000295:instrumentation* / Q000379:methods