| dc.description.abstract | In preclinical small animal experiments of nuclear medicine imaging technology, it is necessary to use imaging equipment with higher spatial resolution than that used for human organ imaging. The goal is to make the reconstructed images of small animal organs have the same precision as the reconstructed images of human organs. This thesis utilizes the Single Photon Emission Microscope (SPEM) as the imaging system to acquire projection images. SPEM is a specialized branch of the Single Photon Emission Computed Tomography (SPECT) with high spatial resolution. It contains a seven-pinhole collimator, a thallium-doped cesium iodide crystal CsI (Tl), an electrostatic de-magnifier tube, and an Electron-Multiplying Charge-Coupled Device (EMCCD).
To achieve high-quality reconstruction of object images in the field of computed tomographic technology, it requires a matrix that establishes the transformation relationship between the object space and the image space, that is, a high-resolution and accurate imaging system matrix. This study aims to establish a more accurate imaging system matrix by improving and optimizing the steps and calculation methods used in our laboratory′s previous imaging system
matrix.
In the past, our laboratory had focused on obtaining the geometric parameters between the detector, the translation stages, and the rotating platform for SPEM. For this purpose, two experiments were conducted: a Geometric Calibration experiment and a Grid-Scan experiment. After these two experiments, we obtained the projection images of point sources at various positions within the object space. By analyzing the projection images of these point sources, we got the point response functions of the object space and simplified them into two-dimensional Gaussian functions with six parameters. These six parameters are flux, x and y centroids of the point source projection, the principal axis angle of the ellipse-like projection image, and the length parameters of the major and minor axes. The x and y centroid coordinates were used to fit the geometric parameters between the detector, the translation stages, and the rotating platform for subsequently obtaining a global coordinate system.
Using this coordinate system in combination with the previously mentioned six Gaussian parameters and the global coordinates of the grid, we first calculated the pinhole-axis fitting. After obtained the pinhole-axis vectors, this study established and improved the previous imaging model from our laboratory. We then used this improved model to create imaging system matrices of different voxel spacings. These different matrices will be used in the Ordered-Subset
Expectation Maximization (OSEM) algorithm to reconstruct the object image. To enhance the resolution and contrast of the reconstructed object images, we applied the shift-variant point response functions and used the deconvolution algorithm during and after the OSEM reconstruction to perform deblurring calculations. Additionally, we compared the differences in reconstruction results between the original OSEM reconstruction, and the reconstructions with the deblurring algorithm during and after the OSEM reconstructions. | en_US |