Improvement of Image Quality in Chest MDCT Using Nonlinear Wavelet Shrinkage with Trimmed-thresholding

Abstract

Multidetector-row computed tomography (MDCT) has dramatically increased the speed of scanning, and allows high-resolution imaging compared with conventional single detector-row CT (SDCT). However, the use MDCT makes use of an increase in volume scanning, and causes a simultaneous increase in radiation dose to the patient. Thus, the radiation dose from the X-ray CT has become a problem in recent years. In this study, nonlinear wavelet-based edge preservation de-noising using trimmed-thresholding was applied to reconstructed low-dose chest MDCT images, and optimal wavelet processing including wavelet functions and thresholding methods was examined. Moreover, the usefulness of the de-noising for reducing radiation dose was examined. As a result of optimized edge preservation de-noising, noise reduction was achieved with little deterioration in image quality, and the wavelet function used at that time was Coiflet's with shorter support. As a result, almost the same quality of reconstructed image of the chest phantom was obtained for conventional scanning and low-dose scanning with the wavelet de-noising method using trimmed- thresholding. That is, the radiation dose from MDCT could be reduced using this wavelet-based de-noising method.