Evaluation of 10 mAs and low-contrast CT image optimization based on the multifractal spectrum in brain of infant

Objective: To analyze scanned image optimization based on the multifractal soectrum and image fractal algorithm of 64-slice spiral CT in brain of infant. Methods: The image data of Toshiba Aquilion 64-slice CT scanning using 10 mAs were imported to image processing toolboxs of Matlab 7.1. The evaluation of multifractal spectrum and image denosing were performed, and compared with image quality of conventional low-dose CT using 50 mAs. Results: The low-contrast scanned image used 10 mAs is the valueless medical image because of serious noise. Image denoise based on the fractal model had superior characteristic of image detail preserving and better contrast-to-noise ratio(CNR). There existed a group difference in the score of image quality between the rude imaging noise and optimized image based on the multifractal spectrum algorithm, though the score was still significantly lower than the normal dosage scanned image (F=38.85, P<0.01). The group difference was also manifested the image quality of infants can achieve basically the request of clinical diagnosis by suitable model denoising algorithm. Conclusions: Image denoising based on the multifractal spectrum model can be used on the low-dose and low-contrast CT image optimization. It improved the CNR of the pathological region. The radiation dose of CT scanning in infants would be declined significantly by its further application in the future. (authors)