@inproceedings{366d4c49d3c040428db50298cffc17e1,
title = "Quantitative evaluation of noise reduction algorithms for very low dose renal CT perfusion imaging",
abstract = "In this paper, we demonstrate a methodology for quantitative evaluation of noise reduction algorithms for very low-dose (1/10 th typical dose) renal CT perfusion imaging. Three types of noise reduction algorithms are evaluated, including the commonly used low pass filtering, edge-preserving algorithms, and spatial-temporal filtering algorithms, such as recently introduced local highly constrained back projection (HYPR-LR) technique and multi-band filtering (MBF). The performance of these noise reduction methods was evaluated in terms of background signal-to-noise ratio (SNR), spatial resolution, fidelity of the time-attenuation curves of renal cortex, and computational speed. The spatial resolution was quantified by an on-scene modulation transfer function (MTF) measurement method. The fidelity of time-attenuation curves was quantified by statistical analysis using a Chi-square test. The results indicate that algorithms employing spatial-temporal correlations of images, such as HYPR and MBF.",
keywords = "Algorithm, Computed tomography, Low dose imaging, Noise reduction",
author = "Xin Liu and Primak, {Andrew N.} and Lifeng Yu and Hua Li and Krier, {James D.} and Lerman, {Lilach O.} and McCollough, {Cynthia H.}",
year = "2009",
doi = "10.1117/12.813777",
language = "English (US)",
isbn = "9780819475091",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
booktitle = "Medical Imaging 2009",
note = "Medical Imaging 2009: Physics of Medical Imaging ; Conference date: 09-02-2009 Through 12-02-2009",
}