Noise assessment across two generations of iterative reconstruction algorithms of three manufacturers using bone reconstruction kernel

J Greffier; J Frandon; A Larbi; D Om; J P Beregi; F Pereira

doi:10.1016/j.diii.2019.08.003

Noise assessment across two generations of iterative reconstruction algorithms of three manufacturers using bone reconstruction kernel

Diagn Interv Imaging. 2019 Dec;100(12):763-770. doi: 10.1016/j.diii.2019.08.003. Epub 2019 Aug 28.

Authors

J Greffier¹, J Frandon², A Larbi², D Om², J P Beregi², F Pereira²

Affiliations

¹ EA 2415, Department of Radiology, Medical Imaging Group Nîmes, University of Montpellier, CHU Nîmes, boulevard du Professeur Robert Debré, 30029 Nîmes cedex, France. Electronic address: joel.greffier@chu-nimes.fr.
² EA 2415, Department of Radiology, Medical Imaging Group Nîmes, University of Montpellier, CHU Nîmes, boulevard du Professeur Robert Debré, 30029 Nîmes cedex, France.

PMID: 31473164
DOI: 10.1016/j.diii.2019.08.003

Abstract

Purpose: To compare the noise-magnitude and noise-texture obtained using strong kernel across two generations of iterative reconstruction (IR) algorithms proposed by three manufacturers.

Materials and methods: Five computed tomography (CT) systems equipped with two generations of IR algorithm (hybrid/statistical IR [H/SIR] or full/partial model-based IR [MBIR]) were compared. Acquisitions on Catphan 600 phantom were performed at 120kV and three dose levels (CTDI_vol: 3, 7 and 12mGy). Raw data were reconstructed using standard "bone" kernel for filtered back projection and one iterative level of two generations of IR algorithms. Contrast-to-noise ratio (CNR) was computed using three regions of interest placed semi-automatically: two placed in the low-density polyethylene and Teflon inserts and another placed on the solid water. Noise power spectrum (NPS) was computed to assess the NPS-peak and noise-texture.

Results: CNR was significantly greater in MBIR compared to H/SIR algorithms for all CT systems (P<0.01). CNR were improved on average from H/SIR to MBIR of 36±14% [SD] (range: 24-57%) for GE-Healthcare, 109±19 [SD] % (range: 89-139%) for Philips Healthcare and 42±5 [SD] % (range: 36-47%) for Siemens Healthineers. The mean NPS peak decreased from H/SIR to MBIR by -41±6 [SD] % (range: -47--35%) for GE Healthcare, -79±3 [SD] % (range: -82--76%) for Philips Healthcare and -52±2 [SD] % (range: -54--51%) for Siemens Healthineers systems. NPS spatial frequencies were greater with MBIR than with H/SIR for Philips Healthcare (20 ± 2 [SD] %; range: 19-22%) and for Siemens Healthineers (9±5 [SD] %; range: 4-14%) but lower for GE Healthcare (-17±3 [SD] %; range: -14--20%).

Conclusion: Using bone kernel with recent MBIR algorithms reduces the noise-magnitude for all CT systems assessed. Noise texture shifted towards high frequency for Siemens Healthineers and Philips Healthcare but the opposite for GE Healthcare.

Keywords: Image quality enhancement; Iterative reconstruction; Multidetector computed tomography; Noise power spectrum; Optimization.

Publication types

Comparative Study

MeSH terms

Algorithms*
Humans
Image Enhancement
Phantoms, Imaging
Radiotherapy Dosage
Signal-To-Noise Ratio*
Tomography, X-Ray Computed*