We have developed a method to remove the noise from the cone beam CT image and consider the reduction of a patient's dose. In diagnostic medicine, cone beam CT increases a patient' exposure dose. The X-ray CT image is degraded by the noise that is called quantum mottle, and the noise becomes so remarkable with decreasing patient' dose. It is known that the image signal can be separated from the noise by measuring the Lipschitz exponents of the image singularities from the evolution of wavelet transform modulus maxima across scales. We identify the singularities of 2-D projections by computing the wavelet transform modulus sum (WTMS) in the direction which is indicated by the phase of wavelet transform. Our preliminary results show the validity of the method based on 2-D WTMS for removing quantum mottle from 2-D projection. And it shows the possibility that the patient's dose can be reduced by this method.
We have examined the characteristic of a flat-panel detector used for our cone-beam CT scanner. We calculated detection efficiency, the modulation transfer function and the noise characteristic of flat-panel detector by the Monte Carlo method, and compared the results with experiment data. From these data, we estimate the relation between the patient dose and signal-to-noise ratio of projection data of CT image. Furthermore, to reduce the patient dose, we have examined the effect of removing the noise from projection degraded by quantum mottle, by the wavelet analysis. Our preliminary results show that de-noising of projection data with wavelet analysis has an effect to reduce the patient dose to less than 1/10, without decreasing the quality of CT image.