【摘 要】
：
In some practical applications,restricted by scanning environment or scanned object,the projection data obtained from CT imaging system is incomplete,which
【出 处】
：
Computational Biomedical Imaging Workshop(2015计算生物医学成像研讨会)
论文部分内容阅读
In some practical applications,restricted by scanning environment or scanned object,the projection data obtained from CT imaging system is incomplete,which leads to the images inexactly reconstructed by traditional reconstruction methods.To solve the reconstruction problem with incomplete projection data,making full use of the sparsity of the gradient magnitude(such as l1 norm or l0 norm of the gradient magnitude)of the CT images,several different reconstruction methods have been developed for different situations such as fan-beam few-view and limited-angle CT,metal artifacts reduction,limited-angle inverse helical cone-beam CT and linear scan cone-beam CT.The experimental results show that the developed reconstruction methods can effectively suppress the artifacts and noise and improve the quality of reconstruction images.
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