WebApr 3, 2012 · A compressive sensing-based statistical interior tomography method is employed to reconstruct each channel in the local spectral imaging chain, where the reconstructed global gray-scale image from the conventional imaging chain served as … WebOct 28, 2024 · Recently, we developed a feature refinement approach for statistical interior computed tomography (CT) reconstruction. Its potential usefulness have been demonstrated for feature preservation of interior tomography with truncated projection measurements. Inspired by this study, the feature refinement (FR) step is applied to PET …
PET Image Reconstruction from Under-sampled Data
WebJunfeng Wu, Xuanqin Mou, Hengyong Yu and Ge Wang; Statistical interior tomography via dictionary learning without assuming an object support; 12th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, p.440-443, June 16-21, 2013. WebA compressive sensing-based statistical interior tomography method is employed to reconstruct each channel in the local spectral imaging chain, where the reconstructed global gray-scale image from the conventional imaging chain served as the initial guess. free benchmark data by industry
Statistical interior tomography. - Europe PMC
WebFeb 27, 2024 · Inverse Problems and Imaging. Both total variation (TV) and Mumford-Shah (MS) functional are broadly used for regularization of various ill-posed problems in the field of imaging and image processing. Incorporating MS functional with TV, we propose a new functional, named as Mumford-Shah-TV (MSTV), for the object image of piecewise … WebJan 16, 2024 · Statistical iterative reconstruction method [ 30, 31] can be used to reconstruct image. The rest paper is organized as follows. We present the projection and backprojection operations based on 3D DD algorithm using the coordinates as geometrical parameters, and also the statistical iterative reconstruction workflow. WebApr 12, 2024 · General circulation models (GCMs) run at regional resolution or at a continental scale. Therefore, these results cannot be used directly for local temperatures and precipitation prediction. Downscaling techniques are required to calibrate GCMs. Statistical downscaling models (SDSM) are the most widely used for bias correction of … free benchmarker