ROI-Wise Material Decomposition in Spectral Photon-Counting CT [article]

Bingqing Xie and Pei Niu and Ting Su and Valérie Kaftandjian and Loic Boussel and Philippe Douek Feng Yang and Philippe Duvauchelle and Yuemin Zhu
2019 arXiv   pre-print
Spectral photon-counting X-ray CT (sCT) opens up new possibilities for the quantitative measurement of materials in an object, compared to conventional energy-integrating CT or dual energy CT. However, achieving reliable and accurate material decomposition in sCT is extremely challenging, due to similarity between different basis materials, strong quantum noise and photon-counting detector limitations. We propose a novel material decomposition method that works in a region-wise manner. The
more » ... d consists in optimizing basis materials based on spatio-energy segmentation of regions-of-interests (ROIs) in sCT images and performing a fine material decomposition involving optimized decomposition matrix and sparsity regularization. The effectiveness of the proposed method was validated on both digital and physical data. The results showed that the proposed ROI-wise material decomposition method presents clearly higher reliability and accuracy compared to common decomposition methods based on total variation (TV) or L1-norm (lasso) regularization.
arXiv:1912.02483v1 fatcat:bjqbapa4s5duvlf4fjdyzctyyi