IP Library Granted Patent US 12,472,382
Granted Patent B2
US 12,472,382 · App. 18/244,272 · Granted Nov 18, 2025

Motion artifact reduction in computed tomography

Inventors: Adam Michal Strzelecki (Daettwil, CH); Dieter Marc Seghers (Zürich, CH); Igor Peterlik (Kuenten, CH); Mathieu Plamondon (Glattbrugg, CH); Pascal Paysan (Basel, CH); Peter N Munro (Daettwil, CH); Philippe Messmer (Zürich, CH)
Assignee: SIEMENS HEALTHINEERS INTERNATIONAL AG
A61N5/1064A61B6/5264A61N5/1049G06T5/77G06T7/11G06T11/008A61B6/4014A61N2005/1061G06T2200/08G06T2207/10081G06T2207/30096G06T2207/30204
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Quick Facts
Patent No.
US 12,472,382
App. No.
18/244,272
Granted
Nov 18, 2025
Kind
B2
Abstract

A reconstructed volume of a region of patient anatomy is processed to reduce motion artifacts in the reconstructed volume. Autosegmentation of high-contrast structures present in an initial reconstructed volume is performed to generate a 3D representation of the high-contrast structures. 2D mask projections are generated by performing forward projection on the 3D representation, where each 2D mask projection includes location information indicating pixels that correspond to the high-contrast structures during the forward projection process. The acquired 2D projections are modified via in-painting to generate corrected 2D projections, where the acquired 2D projections are modified using information from the 2D mask projections. For example, pixels in the acquired 2D projections that are associated with high-contrast moving structures are replaced with low-contrast pixels. These corrected 2D projections are used to produce an improved reconstructed volume with fewer and/or less visually prominent motion artifacts.

Claims (40)

1 . A computer-implemented method of imaging a region of patient anatomy that includes a target volume and one or more high-contrast portions, the method comprising:

based on a set of two-dimensional (2D) acquired projections of the region of patient anatomy and location information indicating pixels that correspond to the one or more high-contrast portions, generating a set of 2D corrected projections of the region of patient anatomy, wherein each 2D corrected projection in the set of 2D corrected projections is generated by removing visual information from a corresponding 2D acquired projection in the set of 2D acquired projections, wherein the visual information is removed from the pixels that correspond to the one or more high-contrast portions;

generating a first reconstructed volume of the region of patient anatomy based on the 2D corrected projections;

generating a set of low-contrast 2D projections of the region of patient anatomy by performing a forward projection process on the first reconstructed volume; and

generating a second reconstructed volume of the region of patient anatomy by:

generating a set of low-artifact 2D projections of the region of patient anatomy by replacing first image information, in pixels of one or more of the 2D acquired projections that correspond to the high-contrast portion, with second image information from corresponding pixels in the low-contrast 2D projections;

modifying the set of low-artifact 2D projections of the region of patient anatomy by including scaled pixels in one or more border regions of each of the one or more low-artifact 2D projections, wherein each border region borders at least one pixel that includes the second image information and wherein each scaled pixel includes scaled image information that is based on the second image information and on third image information from pixels in the low-contrast 2D projections; and

executing a reconstruction algorithm using the set of modified low-artifact 2D projections of the region to generate the second reconstructed volume.

2 . The computer-implemented method of claim 1 , wherein the scaled information included in each scaled pixel is based on second image information associated with one or more pixels that correspond to the high-contrast portion and third image information from one or more pixels in the low-contrast 2D projections.

3 . The computer-implemented method of claim 2 , wherein the scaled information included in each scaled pixel is scaled between the second image information associated with the one or more pixels that correspond to the high-contrast portion and the third image information from the one or more pixels in the low-contrast 2D projections.

4 . The computer-implemented method of claim 1 , further comprising:

reconstructing an initial reconstructed volume of the region of patient anatomy based on the set of 2D acquired projections of the region;

performing an autosegmentation of the one or more high-contrast portions within the initial reconstructed volume of the region of patient anatomy to generate a three-dimensional (3D) representation of the one or more high-contrast portions; and

generating a set of 2D mask projections of the region of patient anatomy by performing a forward projection process on the 3D representation, wherein each 2D mask projection in the set of 2D mask projections includes the location information indicating the pixels that are blocked by the one or more high-contrast portions during the forward projection process performed on the 3D representation.

5 . The computer-implemented method of claim 4 , wherein the corresponding pixels in the low-contrast 2D projections are indicated by the location information.

6 . The computer-implemented method of claim 4 , further comprising blending the second reconstructed volume with image information from the 3D representation that corresponds to the one or more high-contrast portions to generate a third reconstructed volume.

7 . The computer-implemented method of claim 4 , wherein the 3D representation includes the location information of the one or more high-contrast portions.

8 . The computer-implemented method of claim 4 , further comprising, causing the set of acquired 2D projections of the region to be acquired prior to performing the autosegmentation of the one or more high-contrast portions.

9 . The computer-implemented method of claim 1 , wherein the one or more high-contrast portions comprise at least one of a gas bubble or a fiducial marker disposed within the region.

10 . A non-transitory computer-readable storage medium including instructions that, when executed by one or more processors, configure the one or more processors to perform:

based on a set of 2D acquired projections of a region of patient anatomy and location information indicating pixels that correspond to one or more high-contrast portions within the region of patient anatomy, generating a set of 2D corrected projections of the region of patient anatomy, wherein each 2D corrected projection in the set of 2D corrected projections is generated by removing visual information from a corresponding 2D acquired projection in the set of 2D acquired projections, wherein the visual information is removed from the pixels that correspond to the one or more high-contrast portions;

generating a first reconstructed volume of the region of patient anatomy based on the 2D corrected projections;

generating a set of low-contrast 2D projections of the region of patient anatomy by performing a forward projection process on the first reconstructed volume; and

generating a second reconstructed volume of the region of patient anatomy by:

generating a set of low-artifact 2D projections of the region of patient anatomy by replacing first image information, in pixels of one or more of the 2D acquired projections that correspond to the high-contrast portion, with second image information from corresponding pixels in the low-contrast 2D projections;

modifying the set of low-artifact 2D projections of the region of patient anatomy by including scaled pixels in one or more border regions of each of the one or more low-artifact 2D projections, wherein each border region borders at least one pixel that includes the second image information and wherein each scaled pixel includes scaled image information that is based on the second image information and on third image information from pixels in the low-contrast 2D projections;

executing a reconstruction algorithm using the set of modified low-artifact 2D projections of the region to generate the second reconstructed volume.

11 . The non-transitory computer-readable storage medium of claim 10 , wherein the scaled information included in each scaled pixel is based on second image information associated with one or more pixels that correspond to the high-contrast portion and third image information from one or more pixels in the low-contrast 2D projections.

12 . The non-transitory computer-readable storage medium of claim 11 , wherein the scaled information included in each scaled pixel is scaled between the second image information associated with the one or more pixels that correspond to the high-contrast portion and the third image information from the one or more pixels in the low-contrast 2D projections.

13 . The non-transitory computer-readable storage medium of claim 10 , further including additional instructions that, when executed by the one or more processors, configure the one or more processors to perform:

reconstructing an initial reconstructed volume of the region of patient anatomy based on the set of 2D acquired projections of the region;

performing an autosegmentation of the one or more high-contrast portions within the initial reconstructed volume of the region of patient anatomy to generate a three-dimensional (3D) representation of the one or more high-contrast portions; and

generating a set of 2D mask projections of the region of patient anatomy by performing a forward projection process on the 3D representation, wherein each 2D mask projection in the set of 2D mask projections includes the location information indicating the pixels that are blocked by the one or more high-contrast portions during the forward projection process performed on the 3D representation.

14 . The non-transitory computer-readable storage medium of claim 13 , wherein the corresponding pixels in the low-contrast 2D projections are indicated by the location information.

15 . The non-transitory computer-readable storage medium of claim 13 , further including additional instructions that, when executed by the one or more processors, configure the one or more processors to perform blending the second reconstructed volume with image information from the 3D representation that corresponds to the one or more high-contrast portions to generate a third reconstructed volume.

16 . The non-transitory computer-readable storage medium of claim 13 , further including additional instructions that, when executed by the one or more processors, configure the one or more processors to perform causing the set of acquired 2D projections of the region to be acquired prior to performing the autosegmentation of the one or more high-contrast portions.

17 . The computer-implemented method of claim 16 , wherein causing the set of acquired 2D projections to be acquired comprises:

causing a first 2D projection of the region to be acquired while a first high-contrast portion of the one or more high-contrast portions is disposed in a first position within the region of patient anatomy; and

causing a second 2D projection of the region to be acquired while the first high-contrast portion is disposed in a second position within the region.

18 . The non-transitory computer-readable storage medium of claim 13 , wherein the 3D representation includes the location information of the one or more high-contrast portions.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 19, 2023
From: STRZELECKI, ADAM MICHAL; SEGHERS, DIETER MARC; PETERLIK, IGOR; PLAMONDON, MATHIEU; PAYSAN, PASCAL; MUNRO, PETER N; MESSMER, PHILIPPE
To: VARIAN MEDICAL SYSTEMS INTERNATIONAL AG
Reel/Frame 064944/0315 →
CHANGE OF NAME Recorded Sep 19, 2023
From: VARIAN MEDICAL SYSTEMS INTERNATIONAL AG
To: SIEMENS HEALTHINEERS INTERNATIONAL AG
Reel/Frame 064945/0495 →
Continuity (2)
Continuation 17218484 · Mar 31, 2021
Related Publication 20230414968A1 · Dec 28, 2023
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