祝贺常少杰同学的论文被国际权威杂志IEEE TMI接受


2019-06-18

常少杰同学为第一作者的论文“Spectrum Estimation-Guided Iterative Reconstruction Algorithm for Dual Energy CT”被本领域排名第一的国际权威杂志IEEE Transaction on Medical Imaging杂志接受发表,在此表示祝贺!

 

该论文提出了一种基于模型光谱的双能量CT图像迭代重建方法。该算法可以在迭代过程中同时估计X射线光谱和重建基材料物质图像,对于双能量CT具有重要的应用价值。

 

附论文摘要信息:

 

Title: Spectrum Estimation-Guided Iterative Reconstruction Algorithm for Dual Energy CT

 

Authors: Shaojie Chang, Mengfei Li, Hengyong Yu, Xi Chen, Shiwo Deng, Peng Zhang, and Xuanqin Mou

 

Abstract: X-ray spectrum plays a very important role in dual energy computed tomography (DECT) reconstruction. Because it is difficult to measure x-ray spectrum directly in practice, efforts have been devoted into spectrum estimation by using transmission measurements. These measurement methods are independent of the image reconstruction, which bring extra cost and are time consuming. Furthermore, the estimated spectrum mismatch would degrade the quality of the reconstructed images. In this work, we propose a spectrum estimation-guided iterative reconstruction algorithm for DECT which aims to simultaneously recover the spectrum and reconstruct the image. The proposed algorithm is formulated as an optimization framework combining spectrum estimation based on model spectra representation, image reconstruction and regularization for noise suppression. To resolve the multi-variable optimization problem of simultaneously obtaining the spectra and images, we introduce the block coordinate descent (BCD) method into the optimization iteration. Both numerical simulations and physical phantom experiments are performed to verify and evaluate the proposed method. Experimental results validate the accuracy of the estimated spectra and reconstructed images under different noise levels. The proposed method obtains a better image quality compared with the reconstructed images from the known exact spectra, and is robust in noisy data applications.