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Structure propagation restoration for spectral CT

A technology of local structure and projection data, which is applied in the field of spectral projection data and/or spectral image data processing, and can solve problems such as low image quality, high image noise, and reduced clinical value of images

Active Publication Date: 2015-11-04
KONINKLJIJKE PHILIPS NV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Unfortunately, if the image is reconstructed directly from the material line integrals, the image is very noisy
Consequently, the images obtained are of low quality, which may reduce the clinical value of the images

Method used

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  • Structure propagation restoration for spectral CT
  • Structure propagation restoration for spectral CT
  • Structure propagation restoration for spectral CT

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Embodiment Construction

[0020] A method for improving spectral CT image quality using a restoration algorithm that removes noise and / or artifacts from projection data and / or image data for spectral imaging studies while preserving underlying target structures and spectral features is described below. information.

[0021] first reference figure 1 , illustrates a spectral imaging system 100, such as a spectral computed tomography (CT) scanner. The illustrated spectral imaging system 100 utilizes kVp switching as discussed in more detail below to generate spectral projection data. Spectral imaging system 100 includes a generally fixed gantry 102 and a rotating gantry 104 rotatably supported by fixed gantry 102 and rotating about an examination region 106 about a z-axis.

[0022] A radiation source 108 , such as an X-ray tube, rotates with the rotating gantry 104 and emits radiation throughout the examination region 106 . Radiation source voltage controller 110 controls the average or peak emission v...

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Abstract

A method includes obtaining at least one of projection data from a spectral scan or image data generated from the projection data, selecting a local reference dataset from the at least one of the projection data or the image data, determining a noise pattern for the selected reference dataset, estimating underlying local structure from the reference dataset based on the noise pattern, and restoring at least one of the projection data or the image data based on the estimated underlying local structure.

Description

technical field [0001] The following generally relates to spectral projection data and / or spectral image data processing, and more particularly to structure propagation recovery of spectral projection data and / or spectral image data, and is described with particular application to computed tomography (CT). However, the following also applies to other imaging modalities. Background technique [0002] Spectral (or multi-energy) CT has utilized two attenuation values ​​acquired simultaneously at two different photon energies (e.g., with dual-energy CT) to resolve the photoelectric and Compton contributions including the mass attenuation coefficient of the material being scanned, And then the unknown material is identified by its photoelectric and Compton contribution values. This method is well suited for materials such as iodine with k-edge energies close to the average value of the diagnostic energy range. Since any two linearly independent sums of two basis functions span ...

Claims

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Application Information

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IPC IPC(8): A61B6/03A61B6/00G06T11/00
CPCA61B6/032A61B6/482A61B6/5205A61B6/5258G06T11/005G06T2211/408G06T5/70G06T7/0014G06T2207/10081
Inventor L·戈申
Owner KONINKLJIJKE PHILIPS NV