Dynamic MRI is restricted due to the time required to obtain enough data to reconstruct the image sequence. Several undersampled reconstruction techniques have been proposed to reduce the acquisition time. In most of these techniques the nonacquired data are recovered by modeling the temporal information as varying pixel intensities represented in time or in temporal frequencies. Here we propose a new approach that recovers the missing data through a motion estimation of the object elements ("obels," or pieces of tissue) of the image. This method assumes that an obel displacement through the sequence has lower bandwidth than fluctuations in pixel intensities caused by the motion, and thus it can be modeled with fewer parameters. Preliminary results show that this technique can effectively reconstruct (with root mean square (RMS) errors below 4%) cardiac images and joints with undersampling factors of 8 and 4, respectively. Moreover, in the reconstruction process an approximation of the motion vectors is obtained for each obel, which can be used to quantify dynamic information. Key words: dynamic imaging; undersampling; reconstruction; obel; object element; motion Dynamic MRI has become an important technique for studying the time behavior of many dynamic processes. Clinical applications include cardiac imaging (1), contrastenhanced imaging (2), kinematics of joints and organs (3,4), functional MRI (fMRI) (5), and real-time interventional imaging (6). The simultaneous spatial and temporal resolution desired in these applications is limited due to data-acquisition time constraints. An important line of research in this area has been aimed at developing undersampling reconstruction techniques in k-space or in k-t space (7) without significantly compromising image quality. These techniques improve the acquisition time by reducing the number of acquired samples and estimating the missing data by exploiting the high spatiotemporal correlation of dynamic sequences or from prior information.Traditional approaches operate on a discrete k-t space and either treat each frame separately or consider the temporal information as time-varying pixel intensities represented in time or in temporal frequencies. Therefore, each pixel is considered in a constant position over time. These methods include keyhole (8,9), reduced encoding MR imaging with generalized-series reconstruction (RIGR) (10), reduced field of view (rFOV) (11), hybrid technique for dynamic imaging (12), unaliasing by Fourier-encoding the overlaps using the temporal dimension (UNFOLD) (13), sensitivity encoding incorporating temporal filtering (TSENSE) (14), k-t broad-use linear acquisition speed-up technique (k-t BLAST) (15), and reconstruction employing temporal registration (16). In contrast, in this work we are concerned not with the image pixels, but with the continuous position of the object elements (obels) through the dynamic sequence (17,18).We define an obel as a piece of tissue of the object of interest whose intensity is constant over time. In this way,...

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Magnetic resonance imaging (MRI) was used to study the growth and ripening of grape berries for three varieties. The results show that this technique allows the visualization of internal characteristics of berries using noninvasive procedures in order to obtain the volume and degrees Brix distribution within a cluster. Samples of Cabernet Sauvignon, Carmenère, and Chardonnay varieties collected over the 2002 season were analyzed. Calibration models were developed to correlate soluble solids (degrees Brix) against spin-lattice relaxation time t(1) and spin-spin relaxation time t(2). The correlation of degrees Brix and t(1) was R(2) = 0.75 for Cabernet Sauvignon, R(2) = 0.8 for Carmenère, and R(2) = 0.65 for Chardonnay. In the case of t(2) the correlation was significantly lower. Reconstruction techniques for the three-dimensional representation of clusters were developed, allowing an interactive visualization of the bunches. The method also provides volume measurements of single berries and their distribution within the cluster with an accuracy of 3% and R(2) = 0.98. These results show the potential of MRI in the wine industry for both monitoring and research. Not only does it provide quantitative information about the berries such as volume and degrees Brix distributions, but it can also be used to support the sampling procedures by providing a better cluster characterization.

Three-dimensional (3D) k-space trajectories are needed to acquire volumetric images in MRI. While scan time is determined by the trajectory efficiency, image quality and distortions depend on the shape of the trajectories. There are several 3D trajectory strategies for sampling the k-space using rectilinear or curve schemes. Since there is no evidence about their optimality in terms of image quality and acquisition time, a new design method based on missile guidance ideas is explored. Since air-to-air missile guidance shares similar goals and constraints with the problem of k-space trajectory design, a control approach for missiles is used to design a 3D trajectory. The k-space is divided into small cubes, and each one is treated as a target to be sampled. The main goal is to cover the entire space as quickly and efficiently as possible, with good performance under different conditions. This novel design method is compared to other trajectories using simulated and real data.

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