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

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).

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.

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).

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.