Journal of X-Ray Science and Technology - Volume 24, issue 6

Authors: Kano, Toru | Koseki, Michihiko

Article Type: Research Article

Abstract: BACKGROUND: Computed tomography (CT) is an established imaging technology primarily used as a non-invasive diagnostic tool that reconstructs axial images. However, significant problems with metal artifacts remain. A metal artifact is a strong radial noise in an image, which makes it difficult to diagnose patients and inspect products containing metal implants. Historically, studies related to metal artifact reduction used projection data, though the data is not typically saved after processing. OBJECTIVE: This study proposes a new metal artifact reduction algorithm that does not require projection data, for new applications and for accurate diagnostic techniques. METHODS: …The algorithm utilizes reconstructed images and is based on iterative reconstruction. By reproducing an accurate forward projection on simulation and combining it with an iterative calculation, discrepancies causing metal artifacts are eliminated. RESULTS: Validation was completed with numerical phantom models. Our results indicate that the proposed algorithm effectively reduces metal artifacts, even if numerous complex-shaped metal pieces were embedded in the cross-section. CONCLUSIONS: We developed a novel reconstruction algorithm for metal artifact reduction in CT imaging that only requires reconstructed images and projection conditions. Any historical CT data containing metal artifacts could be improved with this method. Show more

Keywords: Computer tomography (CT), metal artifact, image reconstruction, image processing, iterative reconstruction

DOI: 10.3233/XST-160600

Citation: Journal of X-Ray Science and Technology, vol. 24, no. 6, pp. 901-912, 2016

Authors: Omotayo, Azeez | Elbakri, Idris

Article Type: Research Article

Abstract: OBJECTIVE: Iterative algorithms are gaining clinical acceptance in CT. We performed objective phantom-based image quality evaluation of five commercial iterative reconstruction algorithms available on four different multi-detector CT (MDCT) scanners at different dose levels as well as the conventional filtered back-projection (FBP) reconstruction. METHODS: Using the Catphan500 phantom, we evaluated image noise, contrast-to-noise ratio (CNR), modulation transfer function (MTF) and noise-power spectrum (NPS). The algorithms were evaluated over a CTDIvol range of 0.75–18.7 mGy on four major MDCT scanners: GE DiscoveryCT750HD (algorithms: ASIR™ and VEO™); Siemens Somatom Definition AS+ (algorithm: SAFIRE™); Toshiba Aquilion64 (algorithm: AIDR3D™); and Philips …Ingenuity iCT256 (algorithm: iDose4™). Images were reconstructed using FBP and the respective iterative algorithms on the four scanners. RESULTS: Use of iterative algorithms decreased image noise and increased CNR, relative to FBP. In the dose range of 1.3–1.5 mGy, noise reduction using iterative algorithms was in the range of 11%–51% on GE DiscoveryCT750HD, 10%–52% on Siemens Somatom Definition AS+, 49%–62% on Toshiba Aquilion64, and 13%–44% on Philips Ingenuity iCT256. The corresponding CNR increase was in the range 11%–105% on GE, 11%–106% on Siemens, 85%–145% on Toshiba and 13%–77% on Philips respectively. Most algorithms did not affect the MTF, except for VEO™ which produced an increase in the limiting resolution of up to 30%. A shift in the peak of the NPS curve towards lower frequencies and a decrease in NPS amplitude were obtained with all iterative algorithms. VEO™ required long reconstruction times, while all other algorithms produced reconstructions in real time. Compared to FBP, iterative algorithms reduced image noise and increased CNR. CONCLUSIONS: The iterative algorithms available on different scanners achieved different levels of noise reduction and CNR increase while spatial resolution improvements were obtained only with VEO™. This study is useful in that it provides performance assessment of the iterative algorithms available from several mainstream CT manufacturers. Show more

Keywords: Computed tomography, image quality, reconstruction, spatial resolution, contrast, noise, iterative algorithms

DOI: 10.3233/XST-160601

Citation: Journal of X-Ray Science and Technology, vol. 24, no. 6, pp. 913-930, 2016