Abstract: For partial volume correction, the partial volume effect is simulated using patient-specific segmentation. An organ or other object of the patient is segmented using anatomical imaging. For simulation, the locations of the patient-specific object or objects are sub-divided, creating artificial boundaries in the object. A test activity is assigned to each sub-division and forward projected. The difference of the forward projected activity to the test activity provides a location-by-location partial volume correction map. This correction map is used in reconstruction from the measured emissions, resulting in more accurate activity estimation with less partial volume effect.

Abstract: A system and method include training of an artificial neural network to generate a simulated attenuation-corrected reconstructed volume from an input non-attenuation-corrected reconstructed volume, the training based on a plurality of non-attenuation-corrected volumes generated from respective ones of a plurality of sets of two-dimensional emission data and on a plurality of attenuation-corrected reconstructed volumes generated from respective ones of the plurality of sets of two-dimensional emission data.

Abstract: For partial volume correction, the partial volume effect is simulated using patient-specific segmentation. An organ or other object of the patient is segmented using anatomical imaging. For simulation, the locations of the patient-specific object or objects are sub-divided, creating artificial boundaries in the object. A test activity is assigned to each sub-division and forward projected. The difference of the forward projected activity to the test activity provides a location-by-location partial volume correction map. This correction map is used in reconstruction from the measured emissions, resulting in more accurate activity estimation with less partial volume effect.

Abstract: A system and method include acquisition of a plurality of projection images of a subject, each of the projection images associated with a respective projection angle, determination, for each of the projection images, of a center-of-light location in a first image region, determination of a local fluctuation measure based on the determined center-of-light locations, and determination of a quality measure associated with the plurality of projection images based on the local fluctuation measure.

Abstract: A system and method includes acquisition of a plurality of non-attenuation-corrected volumes, each of the non-attenuation-corrected volumes based on a respective one of a plurality of sets of two-dimensional emission data, acquisition of a plurality of attenuation coefficient maps, each of the plurality of attenuation coefficient maps corresponding to a respective one of the plurality of sets of two-dimensional emission data, training of a convolutional network to generate a generated attenuation coefficient map from an input image volume, the training based on the plurality of non-attenuation-corrected volumes and respective ones of the plurality of attenuation coefficient maps, and output of trained kernels of the trained convolutional network to an emission imaging system.

Abstract: In nuclear medical imaging, respiratory motion is corrected. Rather than pairwise estimation of motion from projection views, a sequence-based technique is used to jointly estimate parameters for a motion model across many projection views. In one approach, this sequence-based method is iteratively solved with a maximum likelihood objective function incorporating the motion model. A surrogate respiration signal is used to gate for the joint estimation and used to convert gated motion parameters to temporal motion parameters.

Abstract: For a multi-modal emission tomography system, an improved control system increases the likelihood of optimal image quality, satisfaction of physician goals, and/or avoids repetition in scanning and the corresponding increase in dose burden. The control system is divided into two or more arrangements. One arrangement receives goal information and outputs reconstruction settings and generic scan settings to satisfy the goal information. Another arrangement converts the generic scan settings to emission tomography system-specific scan settings, which are used to detect emissions. The separation of the arrangements allows independent operation so that different system-specific conversions may be used for different systems.

Abstract: In nuclear medical imaging, respiratory motion is corrected. Rather than pairwise estimation of motion from projection views, a sequence-based technique is used to jointly estimate parameters for a motion model across many projection views. In one approach, this sequence-based method is iteratively solved with a maximum likelihood objective function incorporating the motion model. A surrogate respiration signal is used to gate for the joint estimation and used to convert gated motion parameters to temporal motion parameters.

Abstract: In SPECT reconstruction, multi-modal reconstruction is combined with model-based multi-energy image formation. The scatter modeling of the model-based image formation uses resampling to facilitate convolution with the scatter kernels while maintaining resolution for the multi-energy projection. This combination of multi-modal and model-based multi-energy image formation simultaneously addresses the inaccuracy of the image formation process for complicated energy spectra and image blurring due to degradation of resolution. Varying the reconstruction by iteration may provide some of the benefits while reducing computational burden.

Abstract: A system and method include acquisition of a set of tomographic images of a patient volume associated with each of a plurality of timepoints of a first radiopharmaceutical therapy cycle, determination, for each of the plurality of timepoints, of a systematic uncertainty for each of a plurality of regions within the patient volume based on the set of tomographic images associated with the timepoint, determination, for each of the plurality of timepoints, of a quantitative statistical uncertainty based on the set of tomographic images associated with the timepoint, determination of a dose and a dose uncertainty for each of the plurality of regions based on the set of tomographic images, the systematic uncertainty and the quantitative statistical uncertainty for each of the plurality of timepoints, and display of a cumulative dose and cumulative dose uncertainty for each of the plurality of regions based on the dose and the dose uncertainty determined for each of the plurality of regions.

Abstract: A set of first modality data is provided to an intra-reconstruction motion correction method. The set of first modality data includes a plurality of views. A set of second modality data is provided to the method. A motion estimate is generated for each of the plurality of views in the set of first modality data by registering the set of first modality data with the set of second modality data. A motion corrected model of the set of first modality data is generated by a forward projection including the motion estimate.

Abstract: A set of set of first modality data is received including at least one view comprising a plurality of gates. The set of first modality data is received from a first imaging modality of an imaging system. A set of second modality data is received from a second imaging modality of the imaging system. A motion corrected model of the set of first modality data is generated by forward projecting the set of first modality data including a motion estimate. An update factor for each of the plurality of views is generated by comparing at least one of the plurality of gates to the motion corrected model. The motion corrected model is updated by the update factor to generate a motion corrected image.

Abstract: Projection data are acquired by one or more gamma detectors of a medical imaging system. The counts for each projection are binned into time bins to provide respective frames. Using a computer processor, a respective weight factor is computed for each pair of input points among a plurality of input points associated with respective time bins, each input point being an M-dimensional representation of the frame corresponding to the associated time bin for one of the projections. Each weight factor is inversely proportional to a distance computed between the corresponding pair of input points according to an adaptive distance measure that is dependent on the projection data corresponding to said one projection. An N-dimensional surrogate respiratory signal (N<M) is generated based on an optimization of a nonlinear objective function using the weight factors, wherein the surrogate respiratory signal is indicative of patient respiratory activity.

Abstract: Systems and methods for generating corrected emission tomography images are provided. A method includes obtaining a reconstructed image based on emission tomography data of a head of a patient and defining a boundary region in the reconstructed image estimating a position of a skull of the patient in the reconstructed image. The method also includes generating a map of attenuation coefficient values for the reconstructed image based on the boundary region. The reconstructed image can then be adjusted based on the map. In the method, the attenuation coefficient values within the boundary region are selected to correspond to an attenuation coefficient value for bone and the attenuation coefficient values for the portion of the image surrounded by the boundary region are selected to correspond to an attenuation value for tissue.

Abstract: Projection data are acquired for a portion of the body of a patient at multiple views using one or more detectors, the projection data including multiple two dimensional (2D) projections. A 3D image is initialized. For each view among the plurality of views, the 3D image is transformed using a view transformation corresponding to said view to generate an initial transformed image corresponding to said view, and multiple iterations of an MLEM process are performed based on at least the initial transformed image and the projection data. The MLEM process is initialized with the initial transformed image. The 3D image is updated based on an output of the MLEM process.

Abstract: Reconstruction quality is assessed in medical imaging. An amount of local non-uniformity in a distribution of a statistical measure (e.g., MCDF) is determined. The amount indicates a level of reconstruction quality. A more easily understood amount rather than a rendering of MCDF and/or the amount being a function of local artifacts aids a radiologist in recognizing reconstruction quality and determining whether different reconstruction is warranted.

Abstract: In quantitative SPECT with multiple photopeaks, the combination for the multiple photopeaks is performed within or as part of reconstruction rather than post-reconstruction. Reconstruction is performed iteratively, so the combination for the multiple photopeaks is performed within the iteration loop of the reconstruction, such as combining back projected feedback of the different photopeaks for updating the volume.

Abstract: For partial volume correction, the partial volume effect is simulated using patient-specific segmentation. An organ or other object of the patient is segmented using anatomical imaging. For simulation, the locations of the patient-specific object or objects are sub-divided, creating artificial boundaries in the object. A test activity is assigned to each sub-division and forward projected. The difference of the forward projected activity to the test activity provides a location-by-location partial volume correction map. This correction map is used in reconstruction from the measured emissions, resulting in more accurate activity estimation with less partial volume effect.

Abstract: A system and method includes acquisition of a plurality of non-attenuation-corrected volumes, each of the non-attenuation-corrected volumes based on a respective one of a plurality of sets of two-dimensional emission data, acquisition of a plurality of attenuation coefficient maps, each of the plurality of attenuation coefficient maps corresponding to a respective one of the plurality of sets of two-dimensional emission data, training of a convolutional network to generate a generated attenuation coefficient map from an input image volume, the training based on the plurality of non-attenuation-corrected volumes and respective ones of the plurality of attenuation coefficient maps, and output of trained kernels of the trained convolutional network to an emission imaging system.

Abstract: Model-based scatter correction is used in SPECT with a non-parallel-hole collimator. Model-based scatter correction uses scatter kernels based on simulation to model the scatter for a given system and patient. For non-parallel-hole collimators, the measured sensitivity and measured vector maps are used in the modeling of scatter. The measured sensitivity is used to normalize the scatter kernels simulated for a parallel-hole collimator rather than attempting to simulate scatter with the complicated arrangement of holes. The measured vector maps are used to accurately project the model-based scatter sources into a data or emissions space.