Bioluminescence tomography with structural and sparse a priori information

摘要：

Accurate reconstruction the spatial distribution of bioluminescent light source from boundary measurements is a challenging inverse problem. The non-uniqueness and ill-posedness problem associated with non-spectrally resolved BLT was already demonstrated earlier. In order to obtain stable and fast reconstruction, we use sparseness-inducing regularization and structural a priori information to constrain the reconstruction process. In vivo mouse experiments demonstrate that the proposed scheme can accurately localize and quantify source distribution while maintaining solution stability. Especially, the inclusion of spatial priors from X-ray CT can improve the reconstructed image quality dramatically.

关键词： Bioluminescence Tomography sparse regularization LASSO reconstruction algorithm

作者: Xiaowei He Guohua Geng Zhiyong Zhang Jingjing Yu Junxin Wu

作者单位: School of Information Science and Technology Northwest University Xian, China School of Physics and Information Technology Shaanxi Normal University School of Computer Science an Technical Center in the second mud logging office The Bohai Sea drilling Engineering Ltd.,Oil group

会议类型: 国际会议

会议名称: 2011 4th International Conference on Biomedical Engineering and Informatics(第四届生物医学工程与信息学国际会议 BMEI 2011)

会议地点: 上海

会议语种:英文

页码: 167-171

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）