Discriminative Feature Representation to Improve Projection Data Inconsistency for Low Dose CT Imaging
Discriminative Feature Representation to Improve Projection Data Inconsistency for Low Dose CT Imaging
复制标题
用于改善低剂量 CT 成像投影数据不一致性的判别性特征表示
DOI：
10.1109/tmi.2017.2739841
复制
发表时间：
2017-12-01
影响因子：
10.6
通讯作者：
Chen, Wufan
中科院分区：
文献类型：
--
作者：
Liu, Jin;Ma, Jianhua;Chen, Wufan
In low dose computed tomography (LDCT) imaging, the data inconsistency of measured noisy projections can significantly deteriorate reconstruction images. To deal with this problem, we propose here a new sinogram restoration approach, the sinogram- discriminative feature representation (S-DFR) method. Different from other sinogram restoration methods, the proposed method works through a 3-D representation-based feature decomposition of the projected attenuation component and the noise component using a well-designed composite dictionary containing atoms with discriminative features. This method can be easily implemented with good robustness in parameter setting. Its comparison to other competing methods through experiments on simulated and real data demonstrated that the S-DFR method offers a sound alternative in LDCT.
