Technical University Munich, Biological Imaging, Munich, Germany.
J Biomed Opt. 2010 May-Jun;15(3):036006. doi: 10.1117/1.3431101.
The recent development of hybrid imaging scanners that integrate fluorescence molecular tomography (FMT) and x-ray computed tomography (XCT) allows the utilization of x-ray information as image priors for improving optical tomography reconstruction. To fully capitalize on this capacity, we consider a framework for the automatic and fast detection of different anatomic structures in murine XCT images. To accurately differentiate between different structures such as bone, lung, and heart, a combination of image processing steps including thresholding, seed growing, and signal detection are found to offer optimal segmentation performance. The algorithm and its utilization in an inverse FMT scheme that uses priors is demonstrated on mouse images.
最近开发的混合成像扫描仪将荧光分子断层成像（FMT）和 X 射线计算机断层成像（XCT）集成在一起，使得可以利用 X 射线信息作为图像先验信息来改善光学断层成像重建。为了充分利用这种能力，我们考虑了一种在小鼠 XCT 图像中自动快速检测不同解剖结构的框架。为了准确地区分不同的结构，如骨骼、肺和心脏，我们发现结合使用图像处理步骤，包括阈值处理、种子生长和信号检测，可以提供最佳的分割性能。该算法及其在使用先验信息的逆 FMT 方案中的应用在小鼠图像上进行了演示。
