Image processing for spectral CT

摘要

A method includes estimating structure models for a voxel(s) of a spectral image based on a noise model, fitting structure models to a 3D neighborhood about the voxel(s), selecting one of the structure models for the voxel(s) based on the fittings and predetermined model selection criteria, and de-noising the voxel(s) based on the selected structure model, producing a set of de-noised spectral images. Another method includes generating a virtual contrast enhanced intermediate image for each energy image of a set of spectral images corresponding to different energy ranges based on de-noised spectral images, decomposed de-noised spectral images, an iodine map, and a contrast enhancement factor; and generating final virtual contrast enhanced images by incorporating a simulated partial volume effect with the intermediate virtual contrast enhanced images. Also described herein are approaches for generating a virtual non-contrasted image, a bone and calcification segmentation map, and an iodine map for multi-energy imaging studies.

主权项

1. A method, comprising:
estimating a local noise value for one or more voxels of a spectral image of a set of spectral images corresponding to different energy ranges, producing a noise model for the spectral image; estimating local structure models for a voxel of the spectral image based on a corresponding noise model; selecting one of the local structure models for the voxel of the spectral image based on predetermined model selection criteria; and de-noising the voxel of each spectral image of the set of spectral images based on the selected local structure model by replacing a value of the voxel of each spectral image with a value estimated based on the selected local structure model, wherein a plurality of the voxels of a plurality of spectral images in the set of spectral images are de-noised, producing a set of de-noised spectral images.