Abstract: A computer-implemented method for motion compensation of medical imaging data includes estimating, via a processor, non-periodic motion of a myocardium of a heart due to respiration and/or other body movements throughout a positron emission tomography (PET) scan based on list-mode emission data acquired during the PET scan of the heart of a subject. The method also includes performing, via the processor, event-by-event motion-corrected list-mode reconstruction on the list-mode emission data to generate cardiac images with the non-periodic motion removed.

Abstract: Methods and systems are provided for medical imaging systems. In one embodiment, a method for a medical imaging system comprises acquiring emission data during a positron emission tomography (PET) scan of a patient, reconstructing a series of live PET images while acquiring the emission data, and tracking motion of the patient during the acquiring based on the series of live PET images. In this way, patient motion during the scan may be identified and compensated for via scan acquisition and/or data processing adjustments, thereby producing a diagnostic PET image with reduced motion artifacts and increased diagnostic quality.

Abstract: Methods and systems are provided for medical imaging systems. In one embodiment, a method for a medical imaging system comprises acquiring emission data during a positron emission tomography (PET) scan of a patient, reconstructing a series of live PET images while acquiring the emission data, and tracking motion of the patient during the acquiring based on the series of live PET images. In this way, patient motion during the scan may be identified and compensated for via scan acquisition and/or data processing adjustments, thereby producing a diagnostic PET image with reduced motion artifacts and increased diagnostic quality.

Abstract: A method for performing fault-tolerant reconstruction of an image of an object is provided. The method includes acquiring a dataset corresponding to the object via a plurality of sensors, and detecting anomalous data within the dataset based at least in part on a statistical difference between the anomalous data and reference data within the dataset. The anomalous data is acquired by at least a first sensor of the plurality, and the reference data is acquired by at least a second sensor of the plurality that neighbors the first sensor.

Abstract: Methods and systems are provided for interpolating acquired data of a tracer distribution. In one embodiment, a method comprises reconstructing the acquired data, and interpolating the reconstructed data with a surface, wherein a slope of the surface at a data point of the reconstructed data is limited by a value of the data point. In this way, interpolation artifacts around objects with high tracer density may be avoided.

Abstract: A method for performing fault-tolerant reconstruction of an image of an object is provided. The method includes acquiring a dataset corresponding to the object via a plurality of sensors, and detecting anomalous data within the dataset based at least in part on a statistical difference between the anomalous data and reference data within the dataset. The anomalous data is acquired by at least a first sensor of the plurality, and the reference data is acquired by at least a second sensor of the plurality that neighbors the first sensor.

Abstract: Methods and systems are provided for interpolating acquired data of a tracer distribution. In one embodiment, a method comprises reconstructing the acquired data, and interpolating the reconstructed data with a surface, wherein a slope of the surface at a data point of the reconstructed data is limited by a value of the data point. In this way, interpolation artifacts around objects with high tracer density may be avoided.

Abstract: A radiation detection system includes a detector unit and at least one processor. The detector unit is configured to generate signals responsive to radiation events. The at least one processor receives the signals, and is configured to obtain a first count for at least one of the signals corresponding to a first energy window, the first energy window corresponding to values higher than a nominal peak value; obtain a second count for the at least one of the signals corresponding to a second energy window, the second energy window corresponding to values lower than the nominal peak value; obtain at least one auxiliary count for the at least one of the signals corresponding to at least one auxiliary energy window; and adjust a gain applied to the signals based on the first count, the second count, and the at least one auxiliary count.

Abstract: A method for attenuation correction of a phantom image in a PET imaging system includes obtaining raw scan data of a scanned phantom, a non attenuation corrected template image of a stock phantom of like type to the scanned phantom, and an attenuation map of the stock phantom. The method further includes generating a non-attenuation corrected raw image of the scanned phantom based on the raw scan data, registering the template image and attenuation map to the raw image through a rigid image transform, and applying the registered attenuation map to the raw scan data to enable reconstruction of an attenuation corrected final image.

Abstract: A method for attenuation correction of a phantom image in a PET imaging system includes obtaining raw scan data of a scanned phantom, a non attenuation corrected template image of a stock phantom of like type to the scanned phantom, and an attenuation map of the stock phantom. The method further includes generating a non-attenuation corrected raw image of the scanned phantom based on the raw scan data, registering the template image and attenuation map to the raw image through a rigid image transform, and applying the registered attenuation map to the raw scan data to enable reconstruction of an attenuation corrected final image.

Abstract: Apparatus and methods for determining a boundary of an object for positron emission tomography (PET) scatter correction are provided. One method includes obtaining positron emission tomography (PET) data and computed tomography (CT) data for an object. The PET data and CT data is acquired from an imaging system. The method further includes determining a PET data boundary of the object based on the PET data and determining a CT data boundary of the object based on the CT data. The method further includes determining a combined boundary for PET scatter correction. The combined boundary encompasses the PET data boundary and the CT data boundary.

Abstract: Apparatus and methods for determining a boundary of an object for positron emission tomography (PET) scatter correction are provided. One method includes obtaining positron emission tomography (PET) data and computed tomography (CT) data for an object. The PET data and CT data is acquired from an imaging system. The method further includes determining a PET data boundary of the object based on the PET data and determining a CT data boundary of the object based on the CT data. The method further includes determining a combined boundary for PET scatter correction. The combined boundary encompasses the PET data boundary and the CT data boundary.

Abstract: A method includes receiving cine scan data, receiving a plurality of target phases of a periodic waveform, and generating a plurality of images, each image centered at one of the received target phases. A phase shall represent a percentage of a period of a repeating cycle.

Abstract: A method and system for defining at least one of a plurality of acquisition and processing parameters in a tomosynthesis imaging system are disclosed herein. The method involves providing a user interface that allows a user to quickly and easily specify at least one desired characteristic of a reconstructed image. Based on the user-specified image characteristic, at least one of a desired set of acquisition and processing parameters for the tomosynthesis imaging system is automatically defined. The user interface interacts with a processor for deriving acquisition and processing parameters based upon image characteristics specified by the user using a user interface.