IP Library › Granted Patent US 12,094,036
Granted Patent B2
US 12,094,036 · App. 16/931,642 · Granted Sep 17, 2024

Medical image processing apparatus, and nuclear medicine diagnosis apparatus

Inventor: Kenta Moriyasu (Nasushiobara, JP)
Assignee: CANON MEDICAL SYSTEMS CORPORATION
G06T11/005A61B6/037A61B6/04G06T7/0012G06T7/70G06T2207/10104G06T2207/20036G06T2207/20081G06T2207/30004G06T2207/30242
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Quick Facts
Patent No.
US 12,094,036
App. No.
16/931,642
Granted
Sep 17, 2024
Kind
B2
Abstract

A medical image processing apparatus according to an embodiment includes processing circuitry. The processing circuitry is configured to obtain Time-of-Flight (TOF) depiction image data generated on the basis of an annihilation point of a gamma ray. The processing circuitry is configured to output reconstructed Positron Emission computed Tomography (PET) image data on the basis of the TOF depiction image data and a trained model that outputs the reconstructed PET image data on the basis of an input of the TOF depiction image data.

Claims (23)

1. A medical image processing apparatus, comprising:

processing circuitry configured to:

obtain Time-of-Flight (TOF) depiction image data generated on a basis of an annihilation point of a gamma ray, the TOF depiction image data representing a TOF depiction image in which annihilation point indicating a position of occurrence of annihilation event is depicted as a point or a line; and

output reconstructed Positron Emission computed Tomography (PET) image data on a basis of the TOF depiction image data and a trained model that outputs the reconstructed PET image data on a basis of an input of the TOF depiction image data,

wherein the processing circuitry outputs the reconstructed PET image data, on a basis of the trained model corresponding to a type of drug administered for a subject in a scan at a time of acquiring coincidence counting information from which the obtained TOF depiction image data is derived, the trained model being one of a plurality of trained models corresponding to a plurality of types of drugs.

2. The medical image processing apparatus according to claim 1 , wherein the processing circuitry outputs the reconstructed PET image data, on the basis of the trained model generated by learning a plurality of pieces of TOF depiction image data having a plurality of mutually-different noise levels.

3. The medical image processing apparatus according to claim 1 , wherein the processing circuitry obtains the TOF depiction image data based on coincidence counting information acquired with respect to each of sections of a subject.

4. The medical image processing apparatus according to claim 1 , wherein the processing circuitry obtains the TOF depiction image data based on coincidence counting information acquired while a subject is being moved relative to a PET gantry device.

5. The medical image processing apparatus according to claim 1 , wherein the processing circuitry outputs the reconstructed PET image data, on a basis of the trained model corresponding to a site subject to a scan performed at a time of acquiring coincidence counting information from which the obtained TOF depiction image data is derived, the trained model being one of a plurality of trained models corresponding to a plurality of sites of a subject.

6. The medical image processing apparatus according to claim 5 , wherein

the processing circuitry derives site information indicating a site, on a basis of the obtained TOF depiction image data and another trained model that outputs the site information on a basis of an input of the TOF depiction image data, and

the processing circuitry outputs the reconstructed PET image data, on a basis of one of the plurality of trained models that corresponds to the site indicated by the derived site information.

7. The medical image processing apparatus according to claim 5 , wherein

the processing circuitry detects a site from image data in a position that matches a position of the obtained TOF depiction image data, and

the processing circuitry outputs the reconstructed PET image data on a basis of one of the plurality of trained models that corresponds to the detected site.

8. The medical image processing apparatus according to claim 1 , wherein the processing circuitry outputs the reconstructed PET image data, on a basis of the TOF depiction image data, an attenuation coefficient map, and the trained model that outputs the reconstructed PET image data on a basis of inputs of the TOF depiction image data and the attenuation coefficient map.

9. The medical image processing apparatus according to claim 1 , wherein the processing circuitry outputs the reconstructed PET image data, on a basis of the TOF depiction image data, morphological image data, and the trained model that outputs the reconstructed PET image data on a basis of inputs of the TOF depiction image data and the morphological image data.

10. The medical image processing apparatus according to claim 1 , comprising an interface capable of selecting whether the processing circuitry is caused to reconstruct the reconstructed PET image data by implementing a successive approximation reconstruction method or the processing circuitry is caused to derive the reconstructed PET image data by using the TOF depiction image data.

11. A nuclear medicine diagnosis apparatus comprising:

processing circuitry configured to:

acquire Time-of-Flight (TOF) depiction image data generated on a basis of an annihilation point of a gamma ray, the TOF depiction image data representing a TOF depiction image in which annihilation point indicating a position of occurrence of annihilation event is depicted as a point or a line; and

output reconstructed Positron Emission computed Tomography (PET) image data on a basis of the TOF depiction image data and a trained model that outputs the reconstructed PET image data on a basis of an input of the TOF depiction image data,

wherein the processing circuitry outputs the reconstructed PET image data, on a basis of the trained model corresponding to a type of drug administered for a subject in a scan at a time of acquiring coincidence counting information from which the obtained TOF depiction image data is derived, the trained model being one of a plurality of trained models corresponding to a plurality of types of drugs.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 17, 2020
From: MORIYASU, KENTA
To: CANON MEDICAL SYSTEMS CORPORATION
Reel/Frame 053238/0303 →
Priority Claims (1)
JP 2019-132849 · Jul 18, 2019 · national
Continuity (1)
Related Publication 20210019924A1 · Jan 21, 2021
Cited By (1)
US 12,310,773