Compressive X-ray Tomosynthesis based on Exposure Sequence Optimization. (May 2020)

• Record Type: Journal Article
• Authors: Dong, Wang; Xu, Ma; Qile, Zhao; Hao, Xu; Tingfa, Xu
• Is Part Of: Journal of physics. Volume 1550:Number 3(2020)
• Publication Date: 2020-05
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1550/3/032128
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: X-ray tomosynthesis technique can reconstruct three-dimensional object of interest from two-dimensional projection measurements. This paper proposes a compressive X-ray tomosynthesis imaging method to inspect the moving object on the conveyor. Coding masks are used to modulate the intensity distribution of X-ray sources and reduce the radiation dose. Low-cost uniform linear array detector is used to collect measurement data. Considering the rigid motion of the object, the proposed method uses a dynamic imaging model and a reconstruction framework based on the variation of the sensing geometry. Subsequently, an optimization method is proposed to design the exposure sequence of X-ray sources based on the genetic algorithm. Optimizing the exposure sequence can ameliorate the condition of the ill-posed inverse reconstruction problem. Simulations show that the optimized exposure sequence can effectively improve the reconstruction performance of the compressive X-ray tomosynthesis.