IP Library Granted Patent US 10,210,632
Granted Patent B2
US 10,210,632 · App. 15/091,658 · Granted Feb 19, 2019

Structure-compliant noise reduction during multispectral computed tomography imaging

Inventors: Thomas Flohr (Uehlfeld, DE); Steffen Kappler (Effeltrich, DE); Rainer Raupach (Heroldsbach, DE); Harald Schöndube (Erlangen, DE)
Assignee: Siemens Aktiengesellschaft
G06T11/005G06F19/00G06F19/321G06T11/006G06T2211/421G06T2211/424
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Quick Facts
Patent No.
US 10,210,632
App. No.
15/091,658
Granted
Feb 19, 2019
Kind
B2
Abstract

A method for reconstructing image data during CT imaging is described. In the method, a plurality of independent data records of projection measured data are captured. A combined data record is then determined based on the captured data records. In addition, morphological information is determined based on the combined data record. A target data record is also determined based on the captured independent data records. A target image data record is reconstructed based on the target data record and the determined morphological information. An image data determination facility and a computed tomography system are also described.

Claims (44)

1. A method for reconstructing image data during CT imaging, the method comprising:

capturing a plurality of independent data records of projection measurement data;

determining a combined data record based on the captured independent data records, wherein the combined data record comprises a plurality of differently optimized data records with differently weighted sums;

determining morphological information based on the combined data record;

determining a target data record based on the captured independent data records; and

reconstructing a target image data record based on the target data record and the determined morphological information.

2. The method of claim 1 , wherein the independent data records of the projection measured data comprise data records with different recording parameters, different recording time instants, or different recording parameters and different recording time instants.

3. The method of claim 2 , wherein the different recording parameters comprise different x-ray spectra or spectral distributions.

4. The method of claim 1 , wherein the differently weighted sums are weighted in a noise variance-dependent manner.

5. The method of claim 1 , wherein the differently optimized data records are assigned different materials, the differently optimized data records represent a combination of data records assigned to different materials, or the differently optimized data records emerge from the target data record due to removal of data records assigned to certain materials.

6. The method claim 1 , wherein the determining of the morphological information comprises reconstructing a combined image data record and obtaining structural information with aid of edge-selective filters, the structural information describing a strength and a direction of contrast edges.

7. The method of claim 1 , wherein overall structural information is obtained by determining a plurality of differently optimized data records based on individual, differently optimized data records and combining the plurality of differently optimized data records to form the overall structural information.

8. The method of claim 1 , wherein a locally adaptive filter is determined based on the morphological information, and wherein the reconstruction of the target image data record includes filtered back projection, wherein the locally adaptive filter is used as a filter, a locally adaptive filter, or a filter and a locally adaptive filter, the filter being used as a filter after the reconstruction of the target image data record in the image space, the locally adaptive filter based on the morphological information, the filter being used as a filter in reconstruction act of the target image data record via iterative reconstruction.

9. The method claim 8 , wherein the locally adaptive filter comprises a bilateral filter, wherein a domain filter of the locally adaptive filter is locally asymmetrically pronounced such that a filter length parallel to a contrast edge is longer than at right angles to the contrast edge.

10. The method of claim 9 , wherein the iterative reconstruction is used to reconstruct the target image data record, wherein a regularization strength of the iterative reconstruction is locally dependent on the determined morphological information.

11. The method claim 10 , wherein as a target data record, one of the independent data records is selected or one of the independent data records that was obtained by a base material decomposition of the plurality of independent data records is selected, or a projection data record assigned to a time instant of the projection data recording is selected and an average of all captured projection data records over time is determined as a combined data record.

12. An image data determination facility for reconstructing image data during CT imaging, the facility comprising:

an input interface configured to capture a plurality of independent data records of projection measured data;

a data record determination unit configured to determine a combined data record based the captured independent data records;

a structural information determination unit configured to determine morphological information based on the combined data record;

a filter determination unit configured to determine a locally adaptive filter based on the morphological information;

a target data record determination unit configured to determine a target data record based on the captured independent data records; and

a reconstruction unit configured to reconstruct a target image data record based on the target data record using the locally adaptive filter, wherein the reconstruction of the target image data record comprises a filtered back projection,

wherein the locally adaptive filter is configured to be used as a filter, a locally adaptive filter, or a filter and a locally adaptive filter,

wherein the filter is configured to be used as a filter in the reconstruction of the target image data record via iterative reconstruction,

wherein the filter is configured to be used as a filter after the reconstruction of the target image data record in the image space,

wherein the locally adaptive filter comprises a bilateral filter, and

wherein a domain filter of the locally adaptive filter is locally asymmetrically pronounced such that a filter length parallel to a contrast edge is longer than at right angles to the contrast edge.

13. A computed tomography system comprising:

a control facility with an image data determination facility, wherein the image data determination facility comprises:

an input interface for capturing a plurality of independent data records of projection measured data;

a data record determination unit for determining a combined data record based the captured independent data records, wherein the combined data record comprises a plurality of differently optimized data records with differently weighted sums;

a structural information determination unit for determining morphological information based on the combined data record;

a filter determination unit for determining a locally adaptive filter based on the morphological information;

a target data record determination unit for determining a target data record based on the captured independent data records; and

a reconstruction unit for reconstructing a target image data record based on the target data record using the locally adaptive filter.

14. A non-transitory computer-readable medium with stored program sections configured to be read in and executed by a computing unit, and when executed are configured to:

capture a plurality of independent data records of projection measurement data;

determine a combined data record based on the captured independent data records;

determine morphological information based on the combined data record comprising reconstructing the combined image data record and obtaining structural information with the aid of edge-selective filters, wherein the structural information describes the strength and direction of contrast edges, and wherein the structural information is obtained by determining a plurality of differently optimized data records based on individual, differently optimized data records and combining the plurality of differently optimized data records to form the structural information;

determine a target data record based on the captured independent data records; and

reconstruct a target image data record based on the target data record and the determined morphological information.

15. The method of claim 14 , wherein a locally adaptive filter is determined based on the morphological information, and wherein the reconstruction of the target image data record includes filtered back projection, wherein the locally adaptive filter is used as a filter, a locally adaptive filter, or a filter and a locally adaptive filter, the filter being used as a filter after the reconstruction of the target image data record in the image space, a locally adaptive filter based on the morphological information, the filter being used as a filter in reconstruction act of the target image data record via iterative reconstruction.

16. The method claim 15 , wherein the locally adaptive filter comprises a bilateral filter, wherein a domain filter of the locally adaptive filter is locally asymmetrically pronounced such that a filter length parallel to a contrast edge is longer than at right angles to the contrast edge.

Assignments (3)
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 Apr 28, 2022
From: SIEMENS AKTIENGESELLSCHAFT
To: SIEMENS HEALTHCARE GMBH
Reel/Frame 059764/0013 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 9, 2016
From: FLOHR, THOMAS; KAPPLER, STEFFEN; RAUPACH, RAINER; SCHÖNDUBE, HARALD
To: SIEMENS AKTIENGESELLSCHAFT
Reel/Frame 038516/0927 →
Priority Claims (1)
DE 10 2015 206 127 · Apr 7, 2015 · national
Continuity (1)
Related Publication 20160300368A1 · Oct 13, 2016