【摘要】 为了从PET序列低分辨率图像中重建出优质高分辨率图像,提出了一种基于正则化参数的自适应线性斜率超分辨率算法。该算法通过对正则化线性斜率的自适应,更新动态优化代价函数,以降低对PET图像高频成分的抑制。为验证算法的有效性,采用模拟PET序列图像进行实验。实验结果表明,新算法在改善图像空间分辨率上取得良好的效果。更多还原

【Abstract】 In order to reconstruct a high resolution image from the low resolution Positron Emission Tomography(PET) image sequence,an adaptive linear slope algorithm based on the Regularization Parameter(RP) is proposed.This algorithm can adaptively optimize the cost function and reduce the suppression of high frequency component of PET image by adaptively updating linear slope of the RP.The proposed method is performed on simulated PET image sequence.The results of the experience indicate that the proposed algorithm outperforms conventional approaches in the spatial resolution.更多还原