无先验信息的图像重建
Image reconstruction without prior information
摘要：
提出了一种设计线性正问题图像重建算法的新框架。该框架是基于新的概念，保存在图像重建过程中的数据中的信息，而不是补充它与先验信息。该框架提供了一个解释，为什么流行的重建算法的MRI，CT和卷积通常表示为左可逆矩阵。此外，该框架可以用于改进线性反卷积和解决诸如拉普拉斯变换之类的顽固线性逆问题。
英文摘要：
A novel framework for designing image reconstruction algorithms for linear forward problems is proposed. The framework is based on the novel concept of conserving the information in the data during image reconstruction rather than supplementing it with prior information. The framework offers an explanation as to why the popular reconstruction algorithms for MRI, CT and convolution are generally expressible as left invertible matrices. Also, the framework can be used to improve linear deconvolution and tackle such stubborn linear inverse problems as the Laplace transform.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
