13 March 2013 Super-resolution in cardiac MRI using a Bayesian approach
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Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 866932 (2013) https://doi.org/10.1117/12.2007074
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
Acquisition of proper cardiac MR images is highly limited by continued heart motion and apnea periods. A typical acquisition results in volumes with inter-slice separations of up to 8 mm. This paper presents a super-resolution strategy that estimates a high-resolution image from a set of low-resolution image series acquired in different non-orthogonal orientations. The proposal is based on a Bayesian approach that implements a Maximum a Posteriori (MAP) estimator combined with a Wiener filter. A pre-processing stage was also included, to correct or eliminate differences in the image intensities and to transform the low-resolution images to a common spatial reference system. The MAP estimation includes an observation image model that represents the different contributions to the voxel intensities based on a 3D Gaussian function. A quantitative and qualitative assessment was performed using synthetic and real images, showing that the proposed approach produces a high-resolution image with significant improvements (about 3dB in PSNR) with respect to a simple trilinear interpolation. The Wiener filter shows little contribution to the final result, demonstrating that the MAP uniformity prior is able to filter out a large amount of the acquisition noise.
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Nelson Velasco Toledo, Nelson Velasco Toledo, Andrea Rueda, Andrea Rueda, Cristina Santa Marta, Cristina Santa Marta, Eduardo Romero, Eduardo Romero, } "Super-resolution in cardiac MRI using a Bayesian approach", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 866932 (13 March 2013); doi: 10.1117/12.2007074; https://doi.org/10.1117/12.2007074
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