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X-ray computed tomography is an important technique for clinical diagnose and non destructive testing. In many applications a number of image processing steps are needed before the image information can be used. Obtaining a segmentation of the image is one such image processing step and also is important for applications. The conventional approach is to first reconstruct the image and conduct image...
Compressive sensing (CS) MRI aims to accurately reconstruct images from undersampled k-space data. Most CS methods employ analytical sparsifying transforms such as total-variation and wavelets to model the unknown image and constrain the solution space during reconstruction. Recently, nonparametric dictionary-based methods for CS-MRI reconstruction have shown significant improvements over the classical...
In this study,we have developed a three-dimensional (3D) optical flow program that includes a multi-resolution feature and applied to 3D anatomic structure and gross tumor volume (GTV) contour mapping for four-dimensional computed tomography((4D CT) data. Actual 4D CT data sets from one lung cancer patient and one esophageal tumor patient,10 phases were reconstructed per respiratory cycle respectively...
Magnetic field inhomogeneity is a long-standing problem in magnetic resonance imaging (MRI) and spectroscopic imaging (MRSI). Specifically, in MRSI, field inhomogeneity, if not corrected, can cause frequency shifts, line broadening, and lineshape distortions in the spectral peaks. This paper addresses the problem of correcting the field inhomogeneity effects on limited k-space MRSI data. A penalized...
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