Tabu-DART: a dynamic update strategy for efficient discrete algebraic reconstruction

作     者：Frenkel, Daniel Six, Nathanael De Beenhouwer, Jan Sijbers, Jan 

作者机构：Univ Antwerp Dept Phys Univ Pl 1 B-2610 Antwerp Belgium 

出 版 物：《VISUAL COMPUTER》 (视觉计算机)

年 卷 期：2023年第39卷第10期

页      面：4671-4683页

核心收录：

学科分类：08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：FWO SBO project MetroFlex [S004217N] FWO project [G090020N] FWO [11D8319N] 

主　　题：X-ray tomography Reconstruction algorithms Discrete tomography Limited data tomography 

摘      要：In X-ray computed tomography, discrete tomography (DT) algorithms have been successful at reconstructing objects composed of only a few distinct materials. Many DT-based methods rely on a divide-and-conquer procedure to reconstruct the volume in parts, which improves their run-time and reconstruction quality. However, this procedure is based on static rules, which introduces redundant computation and diminishes the efficiency. In this work, we introduce an update strategy framework that allows for dynamic rules and increases control for divide-and-conquer methods for DT. We illustrate this framework by introducing Tabu-DART, which combines our proposed framework with the Discrete Algebraic Reconstruction Technique (DART). Through simulated and real data reconstruction experiments, we show that our approach yields similar or improved reconstruction quality compared to DART, with substantially lower computational complexity.