Skip to Main content Skip to Navigation
Journal articles

3D Coronary Artery Reconstruction by 2D Motion Compensation Based on Mutual Information

Abstract : Background 3D reconstruction of the coronary arteries can provide more information in the interventional surgery. Motion compensation is one kind of the 3D reconstruction method. Methods We propose a novel and complete 2D motion compensated reconstruction method. The main components include initial reconstruction, forward projection, registration and compensated reconstruction. We apply the mutual information (MI) and rigidity penalty (RP) as registration measure. The advanced adaptive stochastic gradient descent (ASGD) is adopted to optimize this cost function. We generate the maximum forward projection by the simplified distance driven (SDD) projector. The compensated reconstruction adopts the MAP iterative reconstruction algorithm which is based on L0 prior. Results Comparing with the ECG-gating reconstruction and other reference method, the evaluation indicates that the proposed 2D motion compensation leads to a better 3D reconstruction for both the rest and stronger motion phases. The algorithm compensates the residual motion and reduces the artifact largely. As the gating window width increases, the overall image noise decreases and the contrast of the vessels improves. Conclusions The proposed method improved the 3D reconstruction quality and reduced the artifact level. The considerable improvement in the image quality results from motion compensation increases the clinical usability of 3D coronary artery. © 2017 AGBM
Complete list of metadatas

https://hal-univ-rennes1.archives-ouvertes.fr/hal-01777691
Contributor : Laurent Jonchère <>
Submitted on : Wednesday, April 25, 2018 - 9:17:51 AM
Last modification on : Monday, July 20, 2020 - 10:42:06 AM

Identifiers

Collections

Citation

S. Li, J.C. Nunes, C. Toumoulin, L. Luo. 3D Coronary Artery Reconstruction by 2D Motion Compensation Based on Mutual Information. Innovation and Research in BioMedical engineering, Elsevier Masson, 2018, 39 (1), pp.69-82. ⟨10.1016/j.irbm.2017.11.005⟩. ⟨hal-01777691⟩

Share

Metrics

Record views

110