Noise aliasing and the 3D NEQ of flat-panel cone-beam CT: Effect of 2D/3D apertures and sampling

Abstract

The ability to tune an imaging system to be optimal for a specific task is an essential component of image quality. This article discusses the ability to tune the noise-equivalent quanta ͑NEQ͒ of cone-beam computed tomography ͑CBCT͒ by managing noise aliasing through binning of data at different points in the reconstruction cascade. The noise power spectrum, modulation transfer function, and NEQ for CBCT are calculated using cascaded systems analysis. Binning is treated as a modular process, insertable between any two stages ͑in both the 2D projection domain and in the 3D reconstruction domain͒, consisting of the application of an aperture, followed by the resampling of data ͑which introduces noise aliasing͒. Several conditions were examined to demonstrate the validity of the model and to describe the effect on the image quality of some common reconstruction and visualization techniques. It was found that when downsampling data for increased reconstruction speed, binning in 2D results in a superior low-frequency NEQ, while binning in 3D results in a superior high-frequency NEQ. Furthermore, visualization procedures such as slice averaging were found not to degrade the NEQ provided the sampling interval is unchanged. Finally methods for reducing noise aliasing by oversampling are examined, and a method to eliminate noise aliasing without increasing reconstruction time is proposed. These results demonstrate the ease with which the NEQ of CBCT can be modified and thus optimized for specific tasks and show how such analysis can be used to improve image quality.

A dedicated cone‐beam CT system for musculoskeletal extremities imaging: Design, optimization, and initial performance characterization

“…The approach provides a general framework that has been applied fairly broadly for modeling and optimization of 2D imaging systems, [15][16][17][18] as well as 3D modalities such as CBCT. 14,[19][20][21] The complete model of a CBCT imaging system 20,22 consists of 13 stages, including: a 2D projection cascade describing the physical processes from interaction of x-rays in the converter to sampling and readout of the detector with additive noise (and optional pixel binning 22 ); and a 3D cascade describing the mathematical processes of filtered backprojection, from log-transform of the projection data to discrete sampling of the 3D reconstruction matrix. 22 The studies reported below were limited to an investigation of the resolution (presampling detector MTF) and DQE inherent to the 2D image acquisition component of the proposed system via the 2D projection model.…”

Fundamental relationship between the noise properties of grating-based differential phase contrast CT and absorption CT: Theoretical framework using a cascaded system model and experimental validation

“…The model presented here does not account for possible limitations caused by the following effects: changes in the NPS due to undersampling, 23,24 reduction of the interferometer efficiency due to small-angle scattering, 70 or spatially varying noise behavior due to divergent beams. [71][72][73] These effects would need to be studied in the future, although experimental results presented in this work suggest that their effects may be negligible.…”

“…As is well known in the modern task-based imaging science framework developed for ACT, [17][18][19][20][21][22][23][24] the characterization of the system's detection performance must include the characterization of the modulation transfer function (MTF) for each link of the entire imaging chain, the three-dimensional (3D) NPS, the target imaging task, and the modeling of the potential confounding effects from variability of the anatomical background. [32][33][34][35][36][37][38] Although the detection tasks will be application specific, the overall system performance can be characterized by combining the MTF, NPS, and signal nature into the generalized spatial-frequency-dependent noise equivalent quanta (NEQ).…”

“…For a conventional absorption x-ray CT imaging system, the noise propagation through the image acquisition, reconstruction, and display have been thoroughly studied in recent years. [17][18][19][20][21][22][23][24] The results have played a pivotal role in attempts to optimize a CT imaging system for a specific imaging task. In this paper, we extend the success of the imaging science in ACT to DPC-CT to provide a foundation for optimizing a DPC-CT imaging system to meet the needs of a medical detection task.…”

Development of a New 3D Reconstruction Algorithm for Computed Tomography (CT)

“…Information derived from NPS can be used to quantify image quality parameters such as noise grain (fine or coarse) or object detectability among others. Different frameworks that make use of the NPS have been treated in the literature: to evaluate the effects produced by sampling [78], by the aperture of the fan beam [79], or optimizing the image quality for a certain spatial frequencies of interest [80]. In the next section a more general multidimensional framework, also present in the literature, will be introduced.…”