Fast Scanning Of Micro-CT System And Denoising Method Research

Micro computed tomography(Micro-CT) technology has been widely used in molecular imaging because of its high spatial resolution, harmless to animal tissue and low cost. At the same time, Micro-CT can provide high resolution anatomical information for other imaging, so it can be integrated with other imaging techniques such as positron emission tomography(PET), single photon emission computed tomography(SPECT) and optical imaging(OI).This thesis was devoted to building a turntable type small animal Micro-CT system, which was used to integrate with PET and OI system for muti-modality fussion. It mainly included the following aspects :1. A turntable type Micro-CT system was set up. Firstly, the design object of the system was presented, and the simulation analyses, including the spatial resolution and field of view, were done before system construction. Then, the Micro-CT system was built. It would be as a subsystem of the PET-OI-CT muti-modality system with high spatial resolution and adjustable field of view. A control software was developed for CT imaging acquisition. Finally, the performance of the system was tested, including movement of the source spot, high contrast spatial resolution, contrast resolution and a mouse experiment was carried out to verify the system performance.2. A fast scanning method was developed. In order to reduce the dose of Micro-CT imaging. The feasibility of the method was confirmed by the theory, and the design of the whole collection process was described detailly, A special phanton experiment was carried out to verify the imaging performance of fast scanning method. At last, the method was used for mouse image acquisition.3. The problem of CT image denoising based on non local means algorithm was studied. Due to the short integral time of the fast scanning method, the image noise was very large, the non local means noise was introduced to reduce the noise. The algorithm was applied to the projection data, the sinogram data and 3D reconstruction data respectively. In these three cases, the noise reduction performance of the algorithm was analyzed. and the advantages and disadvantages of the algorithm were compared. In the end, the algorithm was applied to the fast scanning CT data, and got better noise reduction effect.