Based On Wavelet Local Ct Image Reconstruction Algorithm

In medicine, there is a still growing interest in non-invasive examination techniques which can depict anatomical structures without damaging the human body. Computerized Tomography (CT) is a typical example among these methods. It is based on the principle: under a number of angles, the X-Ray attenuation in a cross section of a human body is measured by detector resulting in a set of profiles. This set of profiles is called the Radon Transform of the object in mathematics. The problem now is to reconstruct a two-dimensional image via inverting its Radon Transform.The Filtered Backprojection (FBP) is the most widely used algorithm currently. This algorithm uses the profiles collected from a number of angles to compute the X-Ray attenuation coefficient of a cross section inside the body, then reconstruct the image of the cross section. However there exists a weakness in this algorithm, that is, the recovery of an image at any fixed point requires the knowledge of all projections of the image. This means that a patient would have to be exposed to a relatively large amount of X-Rays even if it was desired to view only a small part of the patient's body. Thus, searching for a means to reduce exposure, and at the same time to be able to perfectly reconstruct the region of interest (ROI), so-called Local Tomography, has been of great interest recently.This thesis developed an algorithm to reconstruct the wavelet coefficients of an image from the Radon transform data. This algorithm is similar to the conventional filtered backprojection algorithm, except that the filters are now angle dependent, and the backprojection gives us the wavelet coefficients of the reconstruction, which are then used to synthesize the reconstruction. The method uses the properties of wavelet to reconstruct a local region of the cross section of a body, using almost completely local data, therefore reduces the amount of exposure and computations in reconstruction, while has the same quality as filtered backprojection algorithm.