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Quantitative Comparison of Noise Texture Across CT Scanners From Different Vendors


J Solomon

J Solomon*, O Christianson, E Samei, Duke University Medical Center, Durham, NC

TH-E-217BCD-7 Thursday 1:00:00 PM - 2:50:00 PM Room: 217BCD

Purpose: To quantitatively compare noise texture across CT scanners from different vendors using the Noise Power Spectrum (NPS).

Methods: The American College of Radiology CT accreditation phantom (Gammex 464, Gammex, Inc., Middleton, WI) was imaged on two scanners: Discovery CT 750HD (GE Healthcare, Waukesha, WI), and SOMATOM Definition Flash (Siemens Healthcare, Germany), using a consistent acquisition protocol (120 kVp, 5 mm slice thickness, 250/200 mAs, and 22 cm field of view). Images were reconstructed using filtered backprojection and a wide selection of reconstruction kernels. For each image set, the 2D NPS were estimated from the uniform section of the phantom. The spectra were normalized by their integral value, radially averaged, and filtered by the human visual response function. A systematic kernel-by-kernel comparison across vendors was performed by computing the peak locations of the spectra and the root mean square error (RMSE) between the filtered NPS of each kernel. GE and Siemens kernels were compared and kernel pairs that minimized the RMSE and the spectra peak location difference were matched.

Results: The RMSE between the NPS of GE and Siemens kernels varied from 0.01 to 0.30 mm². The GE kernels 'Soft', 'Standard', 'Chest', and 'Lung' closely matched the Siemens kernels 'B35f', 'B43f', 'B46f', and 'B80f' (RMSE<0.03 mm², peak difference<0.02 cycles/mm). The GE 'Bone', 'Bone+', and 'Edge' kernels were all matched to Siemens 'B75f' kernel but with sizeable RMSE and peak differences up to 0.20 mm² and 0.47 cycles/mm respectively. These sizeable RMSE and peak differences corresponded to visually perceivable differences in the noise texture of the images.

Conclusions: It is possible to use the NPS to quantitatively compare noise texture across CT systems. The degree to which similar texture across scanners could be achieved varies and is limited by the kernels available on each scanner.

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