SRR Algorithm Applied In CT Images Reconstruction Research

Medical imaging systems are used to scan patients to obtain valuable information for diagnosis and assisting treatment.However,tiny tissue usually can’t be diagnosed by doctors.In this study,an algorithm was presented to improve image resolution.This article proposed one new method of super resolution reconstruction.The input series low resolution images firstly use Fourier Transformation based image registration to let all the series images be aligned with the reference image via calculating the power spectrum phase difference and from inverse Fourier Transformation of whose peak value to get the estimation of shift.After that the images pixel matrix here will be converted into transform domain and using filter based removing noise which retains the low frequency parts and discards the high frequency parts as most noise will be present in the high frequency area.The Motion filters will also be used to optimize the images.The last step is to use image edge checking method to do the different interpolation according to the area of the images.This article uses the above descried super resolution reconstruction to make post processing for the images outputted by the computed tomography system to enhance the space resolution of final images.Experiments used low dose to scan the phantom to get the low resolution images as the input images and let them be processed by above post processing of super resolution reconstruction.These enhanced images are conducted to evaluate the performance to compare with other methods.The advantage of our proposed approach is that the space resolution of final output images are obviously increased.Experimental results show this method performs quite well in increasing the image resolution by quality evaluation of ISNR and MSSIM.It is concluded that the proposed “Super Resolution Technique” could improve CT images without hardware update.