title: A robust adaptive sampling method for faster acquisition of MR images.
abstract: A robust adaptive k-space sampling method is proposed for faster acquisition and reconstruction of MR images. In this method, undersampling patterns are generated based on magnitude profile of a fully acquired 2-D k-space data. Images are reconstructed using compressive sampling reconstruction algorithm. Simulation experiments are done to assess the performance of the proposed method under various signal-to-noise ratio (SNR) levels. The performance of the method is better than non-adaptive variable density sampling method when k-space SNR is greater than 10dB. The method is implemented on a fully acquired multi-slice raw k-space data and a quality assurance phantom data. Data reduction of up to 60% is achieved in the multi-slice imaging data and 75% is achieved in the phantom imaging data. The results show that reconstruction accuracy is improved over non-adaptive or conventional variable density sampling method. The proposed sampling method is signal dependent and the estimation of sampling locations is robust to noise. As a result, it eliminates the necessity of mathematical model and parameter tuning to compute k-space sampling patterns as required in non-adaptive sampling methods.
authors.affiliation: Biomedical Engineering Group, Department of Applied Mechanics, Indian Institute of Technology Madras, India, 600 036. Electronic address: jaganathanvee@gmail.com.
authors.forename: Jaganathan
authors.initials: J
authors.lastname: Vellagoundar
authors.affiliation: Biomedical Engineering Group, Department of Applied Mechanics, Indian Institute of Technology Madras, India, 600 036. Electronic address: rsreddy@iitm.ac.in.
authors.forename: Ramasubba Reddy
authors.initials: RR
authors.lastname: Machireddy
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000033:anatomy & histology; D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008962:Models, Theoretical; D059629:Signal-To-Noise Ratio
keywords: Adaptive sampling; Compressive sampling MRI; Faster MR imaging; k-space sampling