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X-ray dose reduction in abdominal computed tomography using advanced iterative reconstruction algorithms Ning P; Zhu S; Shi D; Guo Y; Sun MPLoS One 2014[]; 9 (3): e92568OBJECTIVE: This work aims to explore the effects of adaptive statistical iterative reconstruction (ASiR) and model-based iterative reconstruction (MBIR) algorithms in reducing computed tomography (CT) radiation dosages in abdominal imaging. METHODS: CT scans on a standard male phantom were performed at different tube currents. Images at the different tube currents were reconstructed with the filtered back-projection (FBP), 50% ASiR and MBIR algorithms and compared. The CT value, image noise and contrast-to-noise ratios (CNRs) of the reconstructed abdominal images were measured. Volumetric CT dose indexes (CTDIvol) were recorded. RESULTS: At different tube currents, 50% ASiR and MBIR significantly reduced image noise and increased the CNR when compared with FBP. The minimal tube current values required by FBP, 50% ASiR, and MBIR to achieve acceptable image quality using this phantom were 200, 140, and 80 mA, respectively. At the identical image quality, 50% ASiR and MBIR reduced the radiation dose by 35.9% and 59.9% respectively when compared with FBP. CONCLUSIONS: Advanced iterative reconstruction techniques are able to reduce image noise and increase image CNRs. Compared with FBP, 50% ASiR and MBIR reduced radiation doses by 35.9% and 59.9%, respectively.|*Algorithms[MESH]|*Radiation Dosage[MESH]|Humans[MESH]|Image Processing, Computer-Assisted/*methods[MESH]|Male[MESH]|Phantoms, Imaging[MESH]|Radiography, Abdominal/*methods[MESH]|Signal-To-Noise Ratio[MESH]|Tomography, X-Ray Computed/*methods[MESH]|X-Rays[MESH] |
