Abstract: A method and system for reconstructing an image in a time-of-flight (TOF) positron emission tomography (PET) system is provided. The method includes using a reconstructed image to determine predicted timing information. Timing bias data is updated based on received timing information associated with acquired scan data from a PET system and the predicted timing information. The method further includes reconstructing the image, based on the updated timing bias data.

Abstract: The invention is directed to a technique for reconstructing PET scan images. According to one embodiment, the invention relates to a method for reconstructing PET scan images. The method comprises: detecting a plurality of coincidence events in a PET scanner; storing data associated with the plurality of coincidence events in a chronological list based on a detection time for each of the plurality of coincidence events; generating correction data based on scatter coincidence events and random coincidence events in the plurality of coincidence events; and reconstructing one or more PET scan images based at least in part on the chronological list of data and the correction data.

Abstract: A method and system for segmenting structures such as lesions in an image is provided. The method comprises selecting one seed inside a lesion in an image either by a user or automatically. The method further includes deriving a directionally statistical model based on a background region or a foreground region of the lesion and determining candidate voxels along a radial direction. The candidate voxels represent the lesion. The method further includes segmenting the lesion using the candidate voxels.

Abstract: A method and system for calibrating a time of flight (TOF) positron emission tomography (PET) scanner are provided. The method stores acquired scan data from detector pairs including data and timing information. The method further calculates an intensity distribution of emission sources based on the scan data and defines a timing pivot point based on a median of an intensity histogram. The method determines a timing correction for each detector based on the location of the timing pivot point. The positron emission tomography (PET) system further provides a plurality of detectors, used in performing imaging scans, and a processor. The processor is configured to determine a timing correction for each detector.

Abstract: Methods and systems for providing scatter correction in a positron emission tomography (PET) system are provided. The method includes determining a look-up table of scatter sinograms during a PET acquisition scan period. The method further includes scatter correcting acquired scan data obtained during the PET acquisition scan period.

Abstract: Methods and systems for calibrating a positron emission tomography (PET) system are provided. The method includes determining at least one non-acquisition time period for the PET system. The method further includes automatically acquiring calibration data during the at least one non-acquisition time period.

Abstract: Methods and systems for controlling a positron emission tomography (PET) system are provided. The method includes receiving timing information from a PET system during an imaging scan using the PET system. The method further includes processing the received timing information and timing bias information relating to the PET system to control the PET system.

Abstract: A method and system for calibrating a Time of Flight Positron Emission Tomography (TOF PET) system are provided. The method includes storing acquired scan data from detector pairs. The acquired scan data includes image data and timing information. The method further includes reconstructing images using scan data. The method also includes determining a timing correction for each detector based on intensity distribution histograms of emission sources. The system includes a controller, which is configured to perform the above-mentioned method steps.

Abstract: Methods and systems for image overlap correction are provided. The method includes acquiring the emission projection data from a plurality of scan frames that extend across at least a portion of a length of an object being imaged wherein elements of the object lie between a region of overlap between two successive frames. The method further includes iteratively reconstructing a 3D image volume from multi-frame emission projection data by updating an estimate of 3D image volume using emission projection data from the plurality of frames within an iterative reconstruction loop.

Abstract: A method and system for controlling a positron emission tomography (PET) system is disclosed. The method includes acquiring image data and time-of-flight information from a PET system during an imaging scan. Further, the method includes performing scatter correction on the image data using the time-of-flight information.

Abstract: Methods and systems for imaging by using a filter for Time-Of-Flight Positron Emission Tomography (TOF PET) are described. The described methods of imaging a patient by using a positron emission tomography (PET) system includes acquiring a plurality of frames of sinogram data, filtering the acquired sinogram data and back-projecting the filtered sinogram data to form an output image of the patient. The acquired sinogram data defines a line of response (LOR) and a time-of-flight (TOF) measurement that localizes positron annihilation within the patient. The filtering of the acquired sinogram data is performed using the TOF measurement.

Abstract: An apparatus and method for segmenting three-dimensional (3D) medical images containing a region of interest is provided that identifies a first set of seed points within the region of interest and a second set of seed points outside the region of interest. A first sphere is constructed within the region of interest. Voxels contained within the medical image are classified using a spatial constrained fuzzy clustering algorithm. A plurality of second spheres is generated. Ones of the plurality of second spheres are accepted that satisfy the homogeneity function threshold as defined by the spatial constricted fuzzy clustering algorithm. A three-dimensional area is grown that defines the region of interest. The region of interest defined by the three-dimensional area is displayed.

Abstract: In accordance with one aspect of the present technique, an imaging simulator system comprises a processor assembly that includes a time activity module configured to generate a time activity data, an imager module adapted to receive at least one imager parameter and configured to model the acquisition of an imaging system, and a simulator module adapted to receive at least the time activity data, and the imager model and configured to generate simulated sensed data based on the time activity data, and the imager model.

Abstract: A method of tracer evaluation using PET (positron emission tomography), includes introducing the tracer into a small animal; scanning the animal in a large-bore PET scanner; and quantitating a concentration of tracer in a predetermined portion of the animal.

Abstract: A nuclear medicine imaging simulator system is provided for simulating nuclear imaging of a target within a phantom using a selected pharmacokinetic model. The system includes a processor assembly having at least one processor receiving a digital phantom model and a digital pharmacokinetic model, and a dynamic integration module executable on the processor assembly for integrating the pharmacokinetic model with the phantom model to generate a dynamic phantom data representing activity of the pharmacokinetic model within the phantom model over simulated time.

Abstract: An apparatus and method for segmenting three-dimensional (3D) medical images containing a region of interest is provided that identifies a first set of seed points within the region of interest and a second set of seed points outside the region of interest. A first sphere is constructed within the region of interest. Voxels contained within the medical image are classified using a spatial constrained fuzzy clustering algorithm. A plurality of second spheres is generated. Ones of the plurality of second spheres are accepted that satisfy the homogeneity function threshold as defined by the spatial constricted fuzzy clustering algorithm. A three-dimensional area is grown that defines the region of interest. The region of interest defined by the three-dimensional area is displayed.