Motion estimation based on projective information disentanglement for 3D reconstruction of rotational coronary angiography. (May 2023)

• Record Type: Journal Article
• Authors: Liu, Xiujian; Li, Si; Wang, Bin; Xu, Lin; Gao, Zhifan; Yang, Guang
• Is Part Of: Computers in biology and medicine. Volume 157(2023)
• Publication Date: 2023-05
• Subjects: Coronary angiography -- 3D reconstruction -- Motion compensation -- Projection space -- Vessel overlapping; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2023.106743
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: The 2D projection space-based motion compensation reconstruction (2D-MCR) is a kind of representative method for 3D reconstruction of rotational coronary angiography owing to its high efficiency. However, due to the lack of accurate motion estimation of the overlapping projection pixels, existing 2D-MCR methods may still have a certain level of under-sampling artifacts or lose accuracy for cases with strong cardiac motion. To overcome this, in this study, we proposed a motion estimation approach based on projective information disentanglement (PID-ME) for 3D reconstruction of rotational coronary angiography. The reconstruction method adopts the framework of 2D-MCR, which is referred to as 2D-PID-MCR. The PID-ME consists of two parts: generation of the reference projection sequence based on the fast simplified distance driven projector (FSDDP) algorithm, motion estimation and correction based on the projective average minimal distance measure (PAMD) model. The FSDDP algorithm generates the reference projection sequence faster and accelerates the whole reconstruction greatly. The PAMD model can disentangle the projection information effectively and estimate the motion of both overlapping and non-overlapping projection pixels accurately. The main contribution of this study is the construction of 2D-PID-MCR to overcome the inherent limitations of the existing 2D-MCR method. Simulated and clinical experiments show that the PID-ME, consisting of FSDDP and PAMD, can estimate the motion of the projection sequence data accurately and efficiently. Our 2D-PID-MCR method outperforms the state-of-the-art approaches in terms of accuracy and real-time performance. Highlights: The FSDDP algorithm reduces repetitive calculation without decreasing accuracy. The PAMD model disentangles the overlapping projective information. Our 2D-PID-MCR estimates the motion efficiently and precisely for 3D reconstruction.