Literature DB >> 20709478

Improving low-dose abdominal CT images by Weighted Intensity Averaging over Large-scale Neighborhoods.

Yang Chen1, Wufan Chen, Xindao Yin, Xianghua Ye, Xudong Bao, Limin Luo, Qianjing Feng, Yinsheng li, Xiaoe Yu.   

Abstract

PURPOSE: Though highly desirable in radiologic procedures, low-dose CT (LDCT) images tend to be severely degraded by quantum noise and non-stationary artifacts. The purpose of this paper is to improve the abdominal LDCT images by the approach of Weighted Intensity Averaging over Large-scale Neighborhoods (WIA-LN).
MATERIALS AND METHODS: In the implementation of the proposed WIA-LN method, the processed pixel intensities are adaptively calculated as the weighted intensity averaging of the pixels with similar surrounding structures throughout a large-scale neighborhood. Both phantom and clinical abdominal CT images from a 16 detector rows Siemens CT were acquired at standard and 80% reduced tube current time products (150 mAs and 30 mAs corresponding to standard-dose and low-dose protocols, respectively). Visual comparison, statistical qualitative analysis (image quality scores and hepatic cyst diagnosis), and quantitative calculation (noise and contrast-to-noise ratio) are made.
RESULTS: Better vision and quantitative performance are realized using the proposed WIA-LN method. Compared to original LDCT and standard-dose CT (SDCT) images, statistically significant improvement of noise/artifacts suppression, contrast preservation and hepatic cyst detection in LDCT images are achieved by using the proposed method (P<0.05).
CONCLUSION: With the tube current reduced to approximate one-fifth of the standard tube current setting, clinically acceptable images can still be obtained by using the proposed method. Crown
Copyright © 2010. Published by Elsevier Ireland Ltd. All rights reserved.

Mesh:

Year:  2010        PMID: 20709478     DOI: 10.1016/j.ejrad.2010.07.003

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  18 in total

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