A system comprising: a regression model trainer to train a regression model; a pixel identifier to identify a pixel to be reconstructed; an imaging projections data receiver to receive a set of imaging projections; a volume receiver to receive a volume; and a pixel reconstructor including: a pixel mapper to map the pixel on each imaging projection in the set of imaging projections according to an acquisition geometry and to map the pixel onto voxels from the volume according to an acquisition geometry; an adjacent pixel extractor to extract adjacent pixels around each mapped pixel in the imaging projections; an adjacent voxel extractor to extract adjacent voxels around each mapped pixel in the volume; and a regression model feeder to feed the regression model with the extracted adjacent pixel data and the extracted adjacent voxel data to produce a reconstructed value of the pixel, wherein the regression model trainer includes: a Digital Anthropomorphic Phantom, DAP, Modeler including an acquisition simulator, an algorithm creator, and a DAP database; a Computed Tomography, CT, Modeler including an acquisition simulator, an algorithm creator, and a CT database; and an Algorithm Modifier including an acquisition reconstructor and an algorithm database, wherein the regression model trainer is configured to instruct one or more of the DAP Modeler, the CT Modeler and the Algorithm Modifier to perform regression model training. a regression model trainer to train a regression model; a pixel identifier to identify a pixel to be reconstructed; an imaging projections data receiver to receive a set of imaging projections; a volume receiver to receive a volume; and a pixel reconstructor including: a pixel mapper to map the pixel on each imaging projection in the set of imaging projections according to an acquisition geometry and to map the pixel onto voxels from the volume according to an acquisition geometry; an adjacent pixel extractor to extract adjacent pixels around each mapped pixel in the imaging projections; an adjacent voxel extractor to extract adjacent voxels around each mapped pixel in the volume; and a regression model feeder to feed the regression model with the extracted adjacent pixel data and the extracted adjacent voxel data to produce a reconstructed value of the pixel, wherein the regression model trainer includes: a Digital Anthropomorphic Phantom, DAP, Modeler including an acquisition simulator, an algorithm creator, and a DAP database; a Computed Tomography, CT, Modeler including an acquisition simulator, an algorithm creator, and a CT database; and an Algorithm Modifier including an acquisition reconstructor and an algorithm database, wherein the regression model trainer is configured to instruct one or more of the DAP Modeler, the CT Modeler and the Algorithm Modifier to perform regression model training. a pixel mapper to map the pixel on each imaging projection in the set of imaging projections according to an acquisition geometry and to map the pixel onto voxels from the volume according to an acquisition geometry; an adjacent pixel extractor to extract adjacent pixels around each mapped pixel in the imaging projections; an adjacent voxel extractor to extract adjacent voxels around each mapped pixel in the volume; and a regression model feeder to feed the regression model with the extracted adjacent pixel data and the extracted adjacent voxel data to produce a reconstructed value of the pixel, wherein the regression model trainer includes: a Digital Anthropomorphic Phantom, DAP, Modeler including an acquisition simulator, an algorithm creator, and a DAP database; a Computed Tomography, CT, Modeler including an acquisition simulator, an algorithm creator, and a CT database; and an Algorithm Modifier including an acquisition reconstructor and an algorithm database, wherein the regression model trainer is configured to instruct one or more of the DAP Modeler, the CT Modeler and the Algorithm Modifier to perform regression model training.