The k-t broad-use linear acquisition speed-up technique (BLAST) has become widespread for reducing image acquisition time in dynamic MRI. In its basic form k-t BLAST speeds up the data acquisition by undersampling k-space over time (referred to as k-t space). The resulting aliasing is resolved in the Fourier reciprocal x-f space (x ‫؍‬ spatial position, f ‫؍‬ temporal frequency) using an adaptive filter derived from a low-resolution estimate of the signal covariance. However, this filtering process tends to increase the reconstruction error or lower the achievable acceleration factor. This is problematic in applications exhibiting a broad range of temporal frequencies such as free-breathing myocardial perfusion imaging. We show that temporal basis functions calculated by subjecting the training data to principal component analysis (PCA) can be used to constrain the reconstruction such that the temporal resolution is improved. The presented method is called k-t PCA. Magn Reson Med 62:706 -716, 2009.

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Abstract-Conventional ultrasound systems acquire ultrasound data sequentially one image line at a time. The architecture of these systems is therefore also sequential in nature and processes most of the data in a sequential pipeline. This often makes it difficult to implement radically different imaging strategies on the platforms and makes the scanners less accessible for research purposes. A system designed for imaging research flexibility is the prime concern. The possibility of sending out arbitrary signals and the storage of data from all transducer elements for 5 to 10 seconds allows clinical evaluation of synthetic aperture and 3D imaging. This paper describes a real-time system specifically designed for research purposes.The system can acquire multichannel data in real-time from multi-element ultrasound transducers, and can perform some real-time processing on the acquired data. The system is capable of performing real-time beamforming for conventional imaging methods using linear, phased, and convex arrays. Image acquisition modes can be intermixed, and this makes it possible to perform initial trials in a clinical environment with new imaging modalities for synthetic aperture imaging, 2D and 3D B-mode, and velocity imaging using advanced coded emissions.The system can be used with 128-element transducers and can excite 128 transducer elements and receive and sample data from 64 channels simultaneously at 40 MHz with 12-bit precision. Two-to-one multiplexing in receive can be used to cover 128 receive channels. Data can be beamformed in real time using the system's 80 signal processing units, or it can be stored directly in RAM. The system has 16 Gbytes RAM and can, thus, store more than 3.4 seconds of multichannel data. It is fully software programmable and its signal processing units can also be reconfigured under software control. The control of the system is done over a 100-Mbits/s Ethernet using C and Matlab. Programs for doing, e.g., B-mode imaging can be written directly in Matlab and executed on the system over the net from any workstation running Matlab. The overall system concept is presented along with its implementation and examples of B-mode and in vivo synthetic aperture flow imaging.

Three-dimensional myocardial perfusion imaging requires significant acceleration of data acquisition to achieve wholeheart coverage with adequate spatial and temporal resolution. The present article introduces a compartment-based k-t principal component analysis reconstruction approach, which permits three-dimensional perfusion imaging at 10-fold nominal acceleration. Using numerical simulations, it is shown that the compartment-based method results in accurate representations of dynamic signal intensity changes with significant improvements of temporal fidelity in comparison to conventional k-t principal component analysis reconstructions. Comparison of the two methods based on rest and stress threedimensional perfusion data acquired with 2.3 3 2.3 3 10 mm 3 during a 225 msec acquisition window in patients confirms the findings and demonstrates the potential of compartmentbased k-t principal component analysis for highly accelerated three-dimensional perfusion imaging. Magn Reson Med 65:575-587,