It has long been realized that the problem of radar imaging is a special case of image reconstruction in which the data are incomplete and noisy. In other fields, iterative reconstruction algorithms have been used suc...It has long been realized that the problem of radar imaging is a special case of image reconstruction in which the data are incomplete and noisy. In other fields, iterative reconstruction algorithms have been used successfully to improve the image quality. This paper studies the application of iterative algorithms in radar imaging. A discrete model is first derived, and the iterative algorithms are then adapted to radar imaging. Although such algorithms are usually time consuming, this paper shows that, if the algorithms are appropriately simplified, it is possible to realize them even in real time. The efficiency of iterative algorithms is shown through computer simulations.展开更多
Scatter correction in single photon emission computed tomography （SPECT） has been focused on either using multiple-window acquisition technique or the scatter modeling technique in iterative image reconstruction. We...Scatter correction in single photon emission computed tomography （SPECT） has been focused on either using multiple-window acquisition technique or the scatter modeling technique in iterative image reconstruction. We propose a technique that uses ：only the emission data for scatter correction in SPECT. We assume that the scatter data can be approximated by convolving the primary data with a scatter kernel followed by the normalization using the scatter-to-primary ratio （SPR）, Since the emission data is the superposition of the primary data and the scatter data, the convolution normalization process approximately results in the sum of the scatter data and a convolved version of scatter data with the kernel. By applying a proper scaling factor, we can make the estimation approximately equal to or less than the scatter data anywhere in the projection domain. Phantom and patient cardiac SPECT studies show that using the proposed emission-based scatter estimation can effectively reduce the scatter-introduced background in the reconstructed images. And additionally, the computational time for scatter correction is negligible as compared to no scatter correction in iterative image reconstruction.展开更多
文摘It has long been realized that the problem of radar imaging is a special case of image reconstruction in which the data are incomplete and noisy. In other fields, iterative reconstruction algorithms have been used successfully to improve the image quality. This paper studies the application of iterative algorithms in radar imaging. A discrete model is first derived, and the iterative algorithms are then adapted to radar imaging. Although such algorithms are usually time consuming, this paper shows that, if the algorithms are appropriately simplified, it is possible to realize them even in real time. The efficiency of iterative algorithms is shown through computer simulations.
文摘Scatter correction in single photon emission computed tomography （SPECT） has been focused on either using multiple-window acquisition technique or the scatter modeling technique in iterative image reconstruction. We propose a technique that uses ：only the emission data for scatter correction in SPECT. We assume that the scatter data can be approximated by convolving the primary data with a scatter kernel followed by the normalization using the scatter-to-primary ratio （SPR）, Since the emission data is the superposition of the primary data and the scatter data, the convolution normalization process approximately results in the sum of the scatter data and a convolved version of scatter data with the kernel. By applying a proper scaling factor, we can make the estimation approximately equal to or less than the scatter data anywhere in the projection domain. Phantom and patient cardiac SPECT studies show that using the proposed emission-based scatter estimation can effectively reduce the scatter-introduced background in the reconstructed images. And additionally, the computational time for scatter correction is negligible as compared to no scatter correction in iterative image reconstruction.
