Dynamic contrast-enhanced magnetic resonance angiography (DCE MRA) has been widely used as a clinical routine for diagnostic assessment of vascular morphology and hemodynamics. It requires high spatial and temporal resolution to capture rapid variation of DCE signals within a limited imaging time. Subtraction-based approaches are typically employed to selectively delineate arteries while eliminating unwanted background signals. Nevertheless, in the presence of subject motion with time, conventional subtraction approaches suffer from incomplete background suppression that impairs the detectability of arteries. In this work, we propose a novel, DCE MRA method that exploits subspace projection (SP) based angiogram separation for robust background suppression. A new, SP-based DCE signal model is introduced, in which images are decomposed into stationary background tissues, motion-induced artifacts, and DCE angiograms of interest. Constrained image reconstruction with sparsity priors is performed to project motion-induced artifacts onto the predefined subspace while extracting DCE angiograms of interest. Simulations and experimental studies validate that the proposed method outperforms existing techniques with increasing reduction factors in suppressing artifacts and noise.
Bibliographical noteFunding Information:
This research was supported by the Brain Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2016M3C7A1913844).
© 2016 IEEE.
- background suppression
- compressed sensing
- dynamic contrast-enhanced MRA
- magnetic resonance angiography
- magnetic resonance imaging
ASJC Scopus subject areas
- Radiological and Ultrasound Technology
- Computer Science Applications
- Electrical and Electronic Engineering