SEGMENTATION OF DYNAMIC CONTRAST ENHANCED MICRO-CT IMAGES FOR FLUORESCENCE MOLECULAR TOMOGRAPHY RECONSTRUCTION

摘要

The hybrid imaging system combined fluorescence molecular tomography (FMT) and micro-computed tomography (micro-CT) has been widely used in preclinical researches, which can provide molecular and anatomical information simultaneously. FMT reconstruction is known as a highly ill-posed inverse problem. Fortunately, the anatomical structural priors from micro-CT could improve FMT reconstruction. In this paper, we propose a mouse segmentation scheme based on dynamic contrast enhanced (DCE) micro-CT images to build up a heterogeneous mouse model for reconstruction of FMT. DCE micro-CT images are collected after administration of non-ionic iodinated contrast agents. Based on the feature vectors consisting of signal intensities of different time points, the heart, liver, spleen, lung, and kidney are classified into different categories and extracted from separate category by morphological postprocessing. The segmentation method and its utilization in FMT reconstruction is demonstrated in an experiment in vivo. The results suggest that the proposed method can realize high accuracy segmentation of mouse anatomical structures, ultimately improve the reconstruction performance of FMT.