Abstract: An image reconstruction system generates a motion estimation using images that have been reconstructed using AI processing. The system receives listmode data collected by an imaging system and produces two or more histo-images based on the listmode data. The system provides the two or more histo-images to an AI system and receives two or more AI reconstructed images back from the AI system based on the two or more histo-images. The system generates a motion estimation based on the two or more AI reconstructed images.

Abstract: An image reconstruction system generates a motion estimation using images that have been reconstructed using AI processing. The system receives listmode data collected by an imaging system and produces two or more histo-images based on the listmode data. The system provides the two or more histo-images to an AI system and receives two or more AI reconstructed images back from the AI system based on the two or more histo-images. The system generates a motion estimation based on the two or more AI reconstructed images.

Abstract: An image reconstruction system generates de-noised, attenuation corrected, and scatter corrected images using AI processing. The system receives a low-dose PET image and applies a machine learning algorithm via a convolutional neural network to the low-dose PET image to generate an output image. The output image includes correction for scatter and attenuation associated with the image being low-dose. The system provides the output image to a computing device comprising a user interface.

Abstract: Methods for simulating, and correcting for, doubly scattered annihilation gamma-ray photons in both time-of-flight (TOF) and non-TOF positron emission tomography scan data are disclosed.

Abstract: A method for parametric image reconstruction and motion correction using whole-body motion fields includes receiving a nuclear imaging data set including a set of dynamic frames and generating at least one of a whole-body forward motion field and/or a whole-body inverse motion field for at least one frame in the set of frames. An iterative loop is applied to update at least one parameter used in a direct parametric reconstruction and at least one parametric image is generated based on the at least one parameter updated by the iterative loop. The iterative loop includes calculating a frame emission image for the at least one frame, generating a motion-corrected frame emission image based on the at least one whole-body forward motion field or a whole-body inverse motion field, and updating at least one parameter by applying a fit to the motion-corrected frame emission image.

Abstract: Systems and methods to partially-gate PET data include acquisition of first data describing a plurality of coincidences detected during a scan of an object, each of the plurality of coincidences associated with a coincidence time and a line of response, acquisition of a motion signal associated with motion of the object during the scan, determination of lines of response which are associated with a region of the object, determination of time periods of region motion based on the motion signal, modification of the first data to remove coincidences which are associated with the determined lines of response and which are associated with a coincidence time during a time period of region motion, reconstruction of an image of the object based on the modified first data, and display of the image.

Abstract: A method for parametric image reconstruction and motion correction using whole-body motion fields includes receiving a nuclear imaging data set including a set of dynamic frames and generating at least one of a whole-body forward motion field and/or a whole-body inverse motion field for at least one frame in the set of frames. An iterative loop is applied to update at least one parameter used in a direct parametric reconstruction and at least one parametric image is generated based on the at least one parameter updated by the iterative loop. The iterative loop includes calculating a frame emission image for the at least one frame, generating a motion-corrected frame emission image based on the at least one whole-body forward motion field or a whole-body inverse motion field, and updating at least one parameter by applying a fit to the motion-corrected frame emission image.

Abstract: A method of conducting a multi-pass dynamic positron emission tomography (PET) scans using continuous bed motion (CBM) mode is disclosed where the method involves acquiring PET sinogram data using CBM mode as the patient bed is moving in a first direction; acquiring PET sonogram data using CBM mode as the patient bed is moving in a second direction that is opposite from the first direction; and reconstructing 3-D PET image from the acquired PET sonogram data.

Abstract: A method for reconstructing medical images comprises: identifying a plurality of organs in a body of a subject based on an anatomic image; assigning a plurality of voxels in the body to respective ones of the plurality of organs based on the anatomic image; and reconstructing activity images of the body using respectively different processing for the voxels assigned to each respective one of the plurality of organs.

Abstract: A method of processing and reconstructing dynamic positron emission tomography (PET) sinogram data comprises: acquiring PET sinogram data using continuous bed motion having a varying velocity; recording a plurality of position-time coordinate pairs while acquiring the PET sinogram data; determining respective acquisition times of each of a plurality of slices of the image, based on the plurality of position-time coordinates; and reconstructing respective parametric images for each respective slice in the plurality of slices.

Abstract: Methods for simulating, and correcting for, doubly scattered annihilation gamma-ray photons in both time-of-flight (TOF) and non-TOF positron emission tomography scan data are disclosed.

Abstract: A method for reconstructing medical images comprises: identifying a plurality of organs in a body of a subject based on an anatomic image; assigning a plurality of voxels in the body to respective ones of the plurality of organs based on the anatomic image; and reconstructing activity images of the body using respectively different processing for the voxels assigned to each respective one of the plurality of organs.

Abstract: A method of processing and reconstructing dynamic positron emission tomography (PET) sinogram data comprises: acquiring PET sinogram data using continuous bed motion having a varying velocity; recording a plurality of position-time coordinate pairs while acquiring the PET sinogram data; determining respective acquisition times of each of a plurality of slices of the image, based on the plurality of position-time coordinates; and reconstructing respective parametric images for each respective slice in the plurality of slices.

Abstract: A method of conducting a multi-pass dynamic positron emission tomography (PET) scans using continuous bed motion (CBM) mode is disclosed where the method involves acquiring PET sinogram data using CBM mode as the patient bed is moving in a first direction; acquiring PET sonogram data using CBM mode as the patient bed is moving in a second direction that is opposite from the first direction; and reconstructing 3-D PET image from the acquired PET sonogram data.

Abstract: Methods and systems for processing data for medical imaging are disclosed. The method includes obtaining a set of continuous bed motion (CBM) data from a first imaging modality. The set of CBM data includes a plurality of gating signals. A CBM normalization matrix is calculated. The CBM normalization matrix calculation includes the plurality of gating signals. An image is reconstructed from the CBM data and the CBM normalization matrix. The first imaging modality can be a PET imaging device.

Abstract: Methods and systems for processing data for medical imaging are disclosed. The method includes obtaining a set of continuous bed motion (CBM) data from a first imaging modality. The set of CBM data includes a plurality of gating signals. A CBM normalization matrix is calculated. The CBM normalization matrix calculation includes the plurality of gating signals. An image is reconstructed from the CBM data and the CBM normalization matrix. The first imaging modality can be a PET imaging device.