US 10,949,971 B2 · Systems and methods for attenuation correction

Abstract

A method include obtaining at least one first PET image of a subject acquired by a PET scanner and at least one first MR image of the subject acquired by an MR scanner. The method may also include obtaining a target neural network model. The target neural network model may provide a mapping relationship between PET images, MR images, and corresponding attenuation correction data, and output attenuation correction data associated with a specific PET image of the PET images. The method may further include generating first attenuation correction data corresponding to the subject using the target neural network model based on the at least one first PET image and the at least one first MR image of the subject, and determining a target PET image of the subject based on the first attenuation correction data corresponding to the subject.

Claims20

Dependent claims

A system for attenuation correction comprising:

at least one storage device storing executable instructions, and
at least one processor in communication with the at least one storage device, when executing the executable instructions, causing the system to:
obtain at least one first positron emission tomography (PET) image of a subject acquired by a PET scanner;
obtain at least one first magnetic resonance (MR) image of the subject acquired by an MR scanner;
obtain a target neural network model that provides a mapping relationship between at least one second PET image acquired by the PET scanner, at least one second MR image acquired by the MR scanner, and a second attenuation correction data;
express the at least one first PET image of the subject acquired by the PET scanner in a form of a first matrix;
generate, based on the mapping relationship between the second attenuation correction data, the at least one second PET image, and the at least one second MR image, a first attenuation correction data in a form of a second matrix;
and
determine, based on the second matrix, a target PET image of the subject by correcting the first matrix.

6 more elements

A method for attenuation correction implemented by a computing device, the computing device including at least one processor and at least one storage device, the method comprising:

obtaining at least one first PET image of a subject acquired by a PET scanner;
obtaining at least one first MR image of the subject acquired by an MR scanner;
obtaining a target neural network model that provides a mapping relationship between at least one second PET image acquired by the PET scanner, at least one second MR image acquired by the MR scanner, and a second attenuation correction data;
expressing the at least one first PET image of the subject acquired by the PET scanner in a form of a first matrix;
generating, based on the mapping relationship between the second attenuation correction data, the at least one second PET image, and the at least one second MR image, a first attenuation correction data in a form of a second matrix;
and
determining, based on the second matrix, a target PET image of the subject by correcting the first matrix.

4 more elements

Dependencies are inferred from the claim text.

Systems and methods for attenuation correction

Life of this patent

Systems and methods for attenuation correction

Life of this patent

Abstract

Claims20