Minimum Cross-Entropy Reconstruction of PET Images Based on a Content-Adaptive Mesh Model

DAI Xiu-bin; ZHU Hong-qing; SHU Hua-zhong; LUO Li-min

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Minimum Cross-Entropy Reconstruction of PET Images Based on a Content-Adaptive Mesh Model

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- Minimum Cross-Entropy Reconstruction of PET Images Based on a Content-Adaptive Mesh Model
- Acta Electronica Sinica Vol. 34, Issue 11, Pages: 1999-2003(2006)
- 作者机构：
  
  东南大学计算机科学与工程系影像科学与技术实验室,江苏,南京,210096
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391.4
- Published：2006
- 稿件说明：
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DAI Xiu-bin, ZHU Hong-qing, SHU Hua-zhong, et al. Minimum Cross-Entropy Reconstruction of PET Images Based on a Content-Adaptive Mesh Model[J]. Acta Electronica Sinica, 2006, 34(11): 1999-2003.
DOI：

DAI Xiu-bin, ZHU Hong-qing, SHU Hua-zhong, et al. Minimum Cross-Entropy Reconstruction of PET Images Based on a Content-Adaptive Mesh Model[J]. Acta Electronica Sinica, 2006, 34(11): 1999-2003. DOI：

摘要

基于内容的自适应三角形网格模型是描述图像的一种有效方法

本文将网格模型与最小交叉熵算法相结合

并加入先验解剖信息

用于PET图像重建.在本文提出的新算法中

先将投影数据用滤波反投影方法(FBP)生成参考图像

再对参考图像提取网格节点

用加入先验解剖信息的最小交叉熵算法对网格节点灰度值进行迭代计算

最后利用迭代后的网格节点灰度值对象素点进行插值得到重建后的图像.在仿真实验中

将该算法与最大似然方法(MLEM)等算法作比较

并分析了参数对重建结果的影响.

Abstract

Content-adaptive mesh modeling is an efficient method for image representation.In this paper

the minimum cross-entropy algorithm using prior anatomical information

combined with mesh model

was applied to the reconstruction of PET images.In the proposed algorithm

the nodes of mesh model were extracted from a reference image obtained with FBP method;then

the values of the nodes were computed through the minimum cross-entropy algorithm with prior anatomical information.Finally

the whole image was reconstructed by interpolation from the values of the nodes.The performance of the proposed method was tested and compared with other algorithms using a set of simulated data.The effect of the parameters on the result was also studied.

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