IP Library › Granted Patent US 10,820,876
Granted Patent B2
US 10,820,876 · App. 16/391,377 · Granted Nov 3, 2020

Method for generating image data using a computer tomography device, image generating computer, computer tomography device, computer program product and computer-readable data medium

Inventors: Andre Ritter (Neunkirchen am Brand, DE); Rainer Raupach (Heroldsbach, DE)
Assignee: SIEMENS HEALTHCARE GMBH
A61B6/5205A61B6/032G06T7/11G06T11/005G06T2207/10081G06T2207/20084G06T2211/424
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Quick Facts
Patent No.
US 10,820,876
App. No.
16/391,377
Granted
Nov 3, 2020
Kind
B2
Abstract

A method is for generating image data using a computer tomography device. CT raw data is provided. An initial image is produced from the CT raw data. The initial image is segmented into regions based upon anatomical features. An image mask corresponding to the regions in each case is produced for the initial image, the image mask defining an effective region for a respectively assigned mapping rule. The mapping rules are applied in the effective regions defined by the respective image masks, and the image data is generated based upon the initial image processed via the mapping rules.

Claims (17)

1. A method for generating image data using a computer tomography device, comprising: providing CT raw data; producing an initial image from the CT raw data; segmenting the initial image into regions based upon anatomical features; producing a respective image mask for the initial image, for each of the regions, each respective image mask defining an effective region for a respectively assigned mapping rule; applying respectively assigned mapping rules in respective effective regions defined by respective image masks; and generating the image data based upon the initial image processed by the mapping rules, wherein the regions segmented are each assigned a multi-material base comprising materials according to a respective anatomical feature, and wherein a spatial distribution of the materials of a respective multi-material base is determined via a corresponding mapping rule wherein in determining the spatial distribution of the materials of the respective multi-material base, a contribution of the materials to corresponding image values of the initial image is specified, in each case, via the mapping rule.

2. The method of claim 1 , wherein the mapping rule is selected as a function of the anatomical feature assigned to a corresponding region or a multi-material base correspondingly assigned.

3. The method of claim 2 , wherein, in determining a spatial distribution of materials of a respective multi-material base, a contribution of the materials to corresponding image values of the initial image is specified, in each case, via the mapping rule.

4. The method of claim 1 , wherein correction data for specifying corrected image data is generated based upon the regions processed via the corresponding mapping rule.

5. The method of claim 4 , wherein the corrected image data is iteratively specified based upon the correction data.

6. The method of claim 5 , wherein in generating the image data, use is made of an iterative reconstruction in which regularization takes place as a function of the correction data.

7. The method of claim 5 , wherein an iteration step of an iteration includes at least the application of the mapping rules, the generation of the correction data and the generation of corrected image data.

8. The method of claim 4 , wherein an electron density distribution is specified as image data based upon the correction data and the CT raw data.

9. The method of claim 1 , wherein a neural network is used in segmenting the initial image.

10. The method of claim 9 , wherein a deep convolutional neural network is used in segmenting the initial image.

11. The method of claim 1 , wherein the CT raw data is provided as projection image data.

12. A non-transitory computer program product, storing program code for performing the method for image generation of claim 1 when the computer program product is executed on a computer.

13. A non-transitory computer-readable data medium storing program code for performing the method for image generation of claim 1 when the program code is executed on a computer.

14. The method of claim 1 , wherein the mapping rule is selected as a function of the anatomical feature assigned to a corresponding region or a multi-material base correspondingly assigned.

15. The method of claim 1 , wherein correction data for specifying corrected image data is generated based upon the regions processed via a corresponding mapping rule.

16. An image generating computer, comprising: a controller configured to produce an initial image from computed tomography (CT) raw data, segment the initial image into regions based upon anatomical features, produce a respective image mask for the initial image, for each of the regions, each respective image mask defining an effective region for a respectively assigned mapping rule, apply respectively assigned mapping rules in respective effective regions defined by respective image masks, and generate the image data based upon the initial image processed by the mapping rules, wherein the regions segmented are each assigned a multi-material base comprising materials according to a respective anatomical feature, and wherein a spatial distribution of the materials of a respective multi-material base is determined via a corresponding mapping rule wherein, in determining the spatial distribution of the materials of the respective multi-material base, a contribution of the materials to corresponding image values of the initial image is specified, in each case, via the mapping rule.

17. A computer tomography device, comprising the image generating computer of claim 16 .

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 20, 2023
From: SIEMENS HEALTHCARE GMBH
To: SIEMENS HEALTHINEERS AG
Reel/Frame 066267/0346 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 24, 2019
From: RITTER, ANDRE; RAUPACH, RAINER
To: SIEMENS HEALTHCARE GMBH
Reel/Frame 049562/0247 →
Priority Claims (1)
EP 18170877 · May 4, 2018 · regional
Continuity (1)
Related Publication 20190336095A1 · Nov 7, 2019