IP Library › Granted Patent US 12,387,393
Granted Patent B2
US 12,387,393 · App. 18/004,455 · Granted Aug 12, 2025

Magnetic resonance hardware-contributed attenuation in positron emission tomography

Inventors: Paul Schleyer (Knoxville, TN); Emily Anaya (Menlo Park, CA)
Assignee: Siemens Medical Solutions USA, Inc.
G06T11/005A61B6/037A61B6/4417A61B6/5282G01R33/34084G01R33/481G06T7/75A61B6/0407G06T2207/10024G06T2207/20081G06T2207/30004G06T2207/30204
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Quick Facts
Patent No.
US 12,387,393
App. No.
18/004,455
Granted
Aug 12, 2025
Kind
B2
Abstract

PET imaging ( 406 ) accounts for attenuation by MR hardware ( 110 ). A camera ( 112 ) captures the MR hardware ( 110 ) as positioned on or by the patient ( 116 ). For example, MR local coils to be or as positioned between the emission sources in the patient ( 116 ) and the PET detector are optically imaged ( 402 ). Image processing is used to determine ( 404 ) the position of the MR hardware ( 110 ). The attenuation of the MR hardware ( 110 ) is accounted for in attenuation correction for PET imaging ( 402 ) based on the determined position.

Claims (30)

1. A method for positron emission tomography (PET) imaging that accounts for attenuation by magnetic resonance (MR) hardware, the method comprising:

imaging a patient with an optical camera, the imaging capturing an optical image of the patient and the MR hardware;

generating an attenuation coefficient map for the MR hardware relative to the patient from the optical image; and

performing the PET imaging using attenuation correction based, at least in part, on the attenuation coefficient map for the MR hardware.

2. The method of claim 1 , wherein imaging comprises imaging one or more optical fiducials on the MR hardware, and wherein generating comprises determining a position of the MR hardware relative to the patient.

3. The method of claim 1 , wherein generating comprises outputting the attenuation coefficient map as fit to the patient by a machine-learned model receiving the optical image as input.

4. The method of claim 1 , wherein imaging the patient with the optical camera comprises imaging the patient with the optical camera and at least one additional optical camera, and wherein generating comprises generating the attenuation coefficient map from the optical image and at least one additional optical images from the at least one additional optical camera.

5. The method of claim 1 , wherein generating comprises identifying one or more three-dimensional positions of the MR hardware from the optical image using a color-coded marker and/or a visible pattern on the MR hardware.

6. The method of claim 1 , wherein performing comprises reconstructing at least a portion of the patient from emissions, the reconstruction using the attenuation correction where the attenuation coefficient map for the MR hardware is included with attenuation for the portion of the patient.

7. The method of claim 1 , wherein imaging comprises imaging the patient with the camera outside a bore of a combination PET and MR imaging system, the camera directed to a patient bed of the combination PET and MR imaging system.

8. The method of claim 2 , wherein imaging comprises imaging the patient while the patient is outside the bore.

9. The method of claim 1 , wherein generating the attenuation coefficient map comprises generating the attenuation coefficient map of the MR hardware as positioned for the patient from a template map of attenuation of the MR hardware.

10. The method of claim 9 , wherein the MR hardware comprises a flexible local coil, and wherein generating comprises adapting the template to reflect a positioning of the flexible local coil on the patient.

11. The method of claim 10 , wherein adapting comprises recognizing shapes and locations of markers of the flexible local coil in the optical image, determining three-dimensional locations of the markers from the shapes and locations, and fitting the template to the three-dimensional locations.

12. The method of claim 10 , wherein adapting comprises predicting three-dimensional locations of markers of the flexible local coil by a machine-learned model receiving the optical image as input, and fitting the template to the three-dimensional locations.

13. A medical imaging system comprising:

a positron emission tomography imager;

a magnetic resonance imager configured to image a patient using one or more local coils positioned on a patient;

a camera configured to capture an optical image of the patient and the one or more local coils as positioned on the patient; and

a processor configured to correct for attenuation of the one or more local coils based on one or more positions, respectively, identified from the optical image, the correction being for imaging by the positron emission tomography imager.

14. The medical imaging system of claim 13 , wherein the positron emission tomography imager and the magnetic resonance imager share a bore for imaging the patient and wherein the camera is mounted outside the bore and the optical image is captured while the patient is partially outside the bore.

15. The medical imaging system of claim 13 , wherein the one or more local coils comprise flexible local coils, and wherein the processor is configured to identify the one or more positions as three-dimensional positions from markers on the one or more local coils.

16. The medical imaging system of claim 15 , wherein the processor is configured to generate an attenuation coefficient map from a fit of template attenuation coefficient maps to the three-dimensional positions.

17. A method for positron emission tomography (PET) imaging that accounts for attenuation by a magnetic resonance (MR) local coil, the method comprising:

capturing an optical image of the MR local coil as positioned on the patient;

determining a distribution of attenuation from the MR local coil based on the optical image; and

reconstructing a PET image from emissions, the reconstructing including attenuation correction using the distribution of the attenuation from the MR local coil.

18. The method of claim 17 , wherein determining the distribution comprises locating markers on the MR local coil from the optical image and fitting an attenuation template to the located markers.

19. The method of claim 17 , wherein determining the distribution comprises outputting distribution information from a machine-learned model in response to input of the optical information.

20. The method of claim 17 , wherein determining comprises determining a deformation and position of the MR local coil as positioned on the patient for MR imaging, the distribution of attenuation being based on the deformation and position of the MR local coil.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 6, 2023
From: SCHLEYER, PAUL; ANAYA, EMILY
To: SIEMENS MEDICAL SOLUTIONS USA, INC.
Reel/Frame 062290/0775 →
Continuity (2)
Provisional Application 62706806 · Sep 11, 2020
Related Publication 20230298231A1 · Sep 21, 2023
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