A simple approach to measure computed tomography (CT) modulation transfer function (MTF) and noise‐power spectrum (NPS) using the American College of Radiology (ACR) accreditation phantom

Abstract

Purpose:To develop an easily-implemented technique with free publicly-available analysis software to measure the modulation transfer function (MTF) and noise-power spectrum (NPS) of a clinical computed tomography (CT) system from images acquired using a widely-available and standardized American College of Radiology (ACR) CT accreditation phantom. Methods: Images of the ACR phantom were acquired on a Siemens SOMATOM Definition Flash system using a standard adult head protocol: 120 kVp, 300 mAs, and reconstructed voxel size of 0.49 mm × 0.49 mm × 4.67 mm. The radial (axial) MTF was measured using an edge method where the boundary of the third module of the ACR phantom, originally designed to measure uniformity and noise, was used as a circular edge. The 3D NPS was measured using images from this same module and using a previously-described methodology that quantifies noise magnitude and 3D noise correlation. Results: The axial MTF was radially symmetrical and had a value of 0.1 at 0.62 mm −1 . The 3D NPS shape was consistent with the filter-ramp function of filtered-backprojection reconstruction algorithms and previously reported values. The radial NPS peak value was ∼115 HU 2 mm 3 at ∼0.25 mm −1 and dropped to 0 HU 2 mm 3 by 0.8 mm −1 . Conclusions:The authors have developed an easily-implementable technique to measure the axial MTF and 3D NPS of clinical CT systems using an ACR phantom. The widespread availability of the phantom along with the free software the authors have provided will enable many different institutions to immediately measure MTF and NPS values for comparison of protocols and systems.

Evaluation of the tool “Reg Refine” for user‐guided deformable image registration

“…1). The NPS was previously adapted for CT imaging through a specific method of data collection and analysis 12 , 13 . The method relies upon the scanning of a uniform phantom and the selection of several ROIs at an equal radius from the center of a given image.…”

Practical considerations for noise power spectra estimation for clinical CT scanners

“…NPS calculation methods should therefore consider this limitation and attempt to acquire image data samples with more stationary noise properties by varying experimental conditions. One such approach is to employ the concept of a local NPS, 4 , 20 , 21 , 22 only analyzing the noise in a localized region of interest (ROI) where the noise is approximately wide‐sense stationary.…”

“…Previous studies have utilized various square ROI sizes, with side lengths of 128 pixels, 4 , 21 , 22 64 pixels, (23) and 32 pixels (19) . Similarly, multiple background removal methods have been proposed and implemented.…”

“…Similarly, multiple background removal methods have been proposed and implemented. Subtraction of two consecutively acquired image sets is the most common method for background removal, 4 , 20 , 21 but various other background removal methods have also been proposed and implemented, such as the subtraction of a first‐order or second‐order polynomial fit 14 , 22 , 24 to the image data. Little has been done in previous literature either to explain the details of background removal methods or to analyze the effect of different background removal methods on the calculated NPS.…”

“…Little has been done in previous literature either to explain the details of background removal methods or to analyze the effect of different background removal methods on the calculated NPS. Additionally, some studies have opted not to apply a window function prior to Fourier transformation, 21 , 22 while others have applied Hann and rectangular window functions to the data (20) . Moreover, the effect of calculation parameters on the local NPS can vary depending on the CT acquisition and reconstruction parameters.…”