成像体模
稳健性(进化)
蒙特卡罗方法
均方误差
反问题
计算机科学
算法
迭代重建
缩小
数学
生物医学工程
人工智能
数学优化
核医学
医学
统计
数学分析
生物化学
化学
基因
作者
Peng Zhang,Jie Liu,Lin Yin,Yu An,Suhui Zhang,Wei Tong,Hui Hui,Jie Tian
标识
DOI:10.1088/1361-6560/ac8718
摘要
Objective.In this study, we propose the adaptive permissible region based random Kaczmarz method as an improved reconstruction method to recover small carotid atherosclerotic plaque targets in rodents with high resolution in fluorescence molecular tomography (FMT).Approach.We introduce the random Kaczmarz method as an advanced minimization method to solve the FMT inverse problem. To satisfy the special condition of this method, we proposed an adaptive permissible region strategy based on traditional permissible region methods to flexibly compress the dimension of the solution space.Main results.Monte Carlo simulations, phantom experiments, andin vivoexperiments demonstrate that the proposed method can recover the small carotid atherosclerotic plaque targets with high resolution and accuracy, and can achieve lower root mean squared error and distance error (DE) than other traditional methods. For targets with 1.5 mm diameter and 0.5 mm separation, the DE indicators can be improved by up to 40%. Moreover, the proposed method can be utilized forin vivolocating atherosclerotic plaques with high accuracy and robustness.Significance.We applied the random Kaczmarz method to solve the inverse problem in FMT and improve the reconstruction result via this advanced minimization method. We verified that the FMT technology has a great potential to locate and quantify atherosclerotic plaques with higher accuracy, and can be expanded to more preclinical research.
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