CROSS: Cross-Domain Residual-Optimization-Based Structure Strengthening Reconstruction for Limited-Angle CT

被引:5
作者
Hu, Dianlin [1 ,2 ]
Zhang, Yikun [1 ,2 ]
Quan, Guotao [3 ]
Xiang, Jun [4 ]
Coatrieux, Gouenou [5 ]
Luo, Shouhua [6 ]
Coatrieux, Jean-Louis [7 ]
Ji, Xu [1 ,2 ]
Han, Hongbin [8 ,9 ]
Chen, Yang [1 ,2 ]
机构
[1] Southeast Univ, Lab Image Sci & Technol, Nanjing 210096, Peoples R China
[2] Southeast Univ, Sch Comp Sci & Engn, Nanjing 210096, Peoples R China
[3] United Imaging Healthcare Ltd Co, CT RPA Dept, Shanghai 201807, Peoples R China
[4] United Imaging Healthcare Ltd Co, Xray Dept, Shanghai 201807, Peoples R China
[5] IMT Atlantique, Inserm, LaTIM UMR1101, F-29000 Brest, France
[6] Southeast Univ, Dept Biomed Engn, Nanjing 210096, Peoples R China
[7] Ctr Rech Informat Biomed Sino Francais, F-35042 Rennes, France
[8] Peking Univ, Inst Med Technol, Hlth Sci Ctr, Beijing 100191, Peoples R China
[9] Peking Univ Third Hosp, Dept Radiol, Beijing 100191, Peoples R China
基金
中国国家自然科学基金;
关键词
Cross-domain-based processing; data consistency (DC); limited-angle computed tomography (CT) reconstruction; residual-error space regularization; structure enhancement network; COMPUTED-TOMOGRAPHY; IMAGE QUALITY; NETWORK; CNN; TOMOSYNTHESIS;
D O I
10.1109/TRPMS.2023.3242662
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Limited-angle computed tomography (CT) is an effective way for practical scenarios due to its flexibility in various complex scanning conditions. However, incomplete projection data will lead to severe wedge artifacts and degraded images, which significantly lower the diagnostic values. To overcome this problem, we propose a novel method termed cross-domain residual-optimization-based structure strengthening (CROSS) reconstruction for limited-angle CT. The proposed CROSS framework consists of three steps, which are conducted on the image domain and measurement domain alternatively. Differing from traditional dual-domain-based algorithms, our CROSS method not only regularizes the reconstruction results on the image space but also the residual-error space, which boosts organ recovery where the area has a larger attenuation coefficient. Besides, the structure-strengthening network is adopted to enhance tissue preservation. Simulated and preclinical datasets are conducted to evaluate the proposed CROSS method. Experiments show that the proposed framework could produce a better performance in artifact removal and edge preservation.
引用
收藏
页码:521 / 531
页数:11
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