在荧光分子断层图像重建过程中，对于生物组织体内具有相同光学参数、相同深度，但不同体积的荧光团，重建出的荧光团光学参数存在较大误差。提出了一种基于体积补偿的荧光分子断层图像重建算法。该算法利用改进的迭代自组织数据分析技术(ISODATA)，设计了初始聚类中心选择和初始期望聚类个数确定的方法，对预迭代的重建图像进行聚类分析。根据聚类得出的荧光团体积大小，设计了一种基于对数运算的体积权值系数计算方法，对重建的荧光光学参数进行非线性补偿。仿真实验结果表明，非线性补偿方法能够较好地修正因荧光团体积大小不一而造成的图像重建误差，显著提高重建图像的质量。

In the process of fluorescence molecular tomography reconstruction, there are different optical parameters in the reconstructed image for the fluorescent targets with the same optical parameters, the same embedded depth, but different volumes in the tissues. To solve this problem, we propose a novel fluorescence molecular tomography reconstruction algorithm based on volume compensation. We use an improved iterative self-organized data analysis techniques algorithm (ISODATA) to decide the center and the expectation number of the initial clusters and to make a cluster analysis of the pre-iterative reconstruction image. According to the sizes of different fluorophores clustered by the improved ISODATA, we design an operational method with volume weight coefficient based on logarithm to compensate nonlinearly the reconstructed optical parameters of different fluorophores. The simulation results show that our compensation method can effectively amend the reconstruction error resulted from the volume difference of the fluorophore.