Abstract: Embodiments of the present disclosure provide a Bayesian image denoising method based on a distribution constraint of noiseless images from a distribution of noisy images. The method includes: determining a distribution constraint of noiseless images from a distribution of noisy images; and performing Bayesian denoising on noisy images based on the distribution constraint of noiseless images.

Abstract: Embodiments of the present disclosure provide a Bayesian image denoising method based on a distribution constraint of noiseless images from a distribution of noisy images. The method includes: determining a distribution constraint of noiseless images from a distribution of noisy images; and performing Bayesian denoising on noisy images based on the distribution constraint of noiseless images.

Abstract: An image-guided radiation therapy apparatus comprises: a high-energy ray source configured for radiation therapy of an object; and a KV ray source, a first and second PET detectors, and a CT detector for KV CT and PET imaging for guiding the radiation therapy. The KV ray source is placed on, or at an inner or outer side of the first PET detector; the second PET detector and the CT detector are configured to receive the KV ray to perform KV CT imaging; the PET detectors are further configured to receive gamma ray emitted by the object to perform PET imaging.

Abstract: Disclosed herein are methods for reducing beam-hardening artifacts in CT imaging using a mapping operator that comprises a hybrid spectral model that incorporates air scan X-ray intensity data acquired at two different effective mean energies. In one variation, the air scan X-ray intensity data acquired during a calibration session is combined with an ideal spectral model for each X-ray detector to derive the hybrid spectral mode. A mapping operator based on the hybrid spectral model is used to correct beam-hardening artifacts in the acquired CT projection data. In some variations, the mapping operator is a lookup table of monochromatic (corrected) projection values, and the acquired CT projection data is used to calculate the index of the lookup table entry that contains the corrected projection value that corresponds with the acquired CT projection data.

Abstract: A tomographic imaging and image-guided radiation therapy apparatus comprises: a high-energy ray source, at least one KV ray source, a first PET detector, a second detector, and a CT detector. The KV ray source is placed on or at an inner side of or at outer side of the first PET detector; the second PET detector and the CT detector are configured to receive the KV ray to perform a KV CT imaging; the first and the second PET detectors are further configured to receive a gamma ray emitted by an object to perform a PET imaging; the high-energy ray source is configured for radiation therapy of the object; the KV CT imaging and/or the PET imaging are configured to assist and/or guide the radiation therapy of the object.

Abstract: There is set forth herein a method including performing with an X-ray detector array of a CT imaging system one or more calibration scans, wherein the one or more calibration scans include obtaining for each element of the first through Nth elements of the X-ray detector array one or more calibration measurements; and updating a spectral response model for each element of the first through Nth elements using the one or more calibration measurements. In another aspect, a CT imaging system can perform imaging, e.g. including material decomposition (MD) imaging, using updated spectral response models for elements of an X-ray detector array. The spectral response models can be updated using a calibration process so that different elements of an X-ray detector array have different spectral response models.

Abstract: Various methods and systems for weighting material density images based on the material imaged are disclosed. In one embodiment, a method for dual energy imaging of a material comprises generating an odd material density image, generating an even material density image, applying a first weight to the odd material density image and a second weight to the even material density image, and generating a material density image based on a combination of the weighted odd material density image and the weighted even material density image. In this way, the image quality may be improved without increasing a radiation dosage.

Abstract: There is set forth herein a method including performing with an X-ray detector array of a CT imaging system one or more calibration scans, wherein the one or more calibration scans include obtaining for each element of the first through Nth elements of the X-ray detector array one or more calibration measurements; and updating a spectral response model for each element of the first through Nth elements using the one or more calibration measurements. In another aspect, a CT imaging system can perform imaging, e.g. including material decomposition (MD) imaging, using updated spectral response models for elements of an X-ray detector array. The spectral response models can be updated using a calibration process so that different elements of an X-ray detector array have different spectral response models.

Abstract: Methods and systems are provided for boosting the contrast levels in an image reconstructed from projection data acquired at a single energy. In one embodiment, a method comprises modifying projection data corresponding to a material based on an absorption behavior of the material at a selected energy, wherein the projection data is acquired at an energy higher than the selected energy. In this way, contrast levels may be enhanced in an image reconstructed from projection data acquired at a typical single energy as though the image were reconstructed from projection data acquired at a lower energy.

Abstract: Systems and methods for iterative multi-material correction are provided. A system includes an imager that acquires projection data of an object. A reconstructor reconstructs the acquired projection data into a reconstructed image, utilizes the reconstructed image to perform a multi-material correction on the acquired projection data to generate a multi-material corrected reconstructed image, and utilizes the multi-material corrected reconstructed image to perform one or more iterations of the multi-material correction on the projection data to generate an iteratively corrected multi-material corrected image.

Abstract: Various methods and systems for dual energy spectral computed tomography imaging are provided. In one embodiment, a method for dual energy imaging comprises generating an image from a higher energy dataset and an updated lower energy dataset, wherein the updated lower energy dataset comprises a combination of a lower energy dataset and a pseudo projection dataset generated from the higher energy dataset. In this way, a weak low energy signal may be recovered, thereby enabling image reconstruction in spite of photon starvation and sparse views.

Abstract: Various methods and systems for spectral computed tomography imaging are provided. In one embodiment, a method comprises acquiring a first projection dataset and a second projection dataset, detecting a location of metal in the first projection dataset, applying corrections to the first and second projection datasets based on the location of the metal, and displaying an image reconstructed from the corrected first and second projection datasets. In this way, metal artifacts may be substantially reduced in dual or multi-energy CT imaging.

Abstract: Various methods and systems for spectral computed tomography imaging are provided. In one embodiment, a method comprises acquiring a first projection dataset and a second projection dataset, detecting a location of metal in the first projection dataset, applying corrections to the first and second projection datasets based on the location of the metal, and displaying an image reconstructed from the corrected first and second projection datasets. In this way, metal artifacts may be substantially reduced in dual or multi-energy CT imaging.

Abstract: A method is provided including acquiring imaging data of an object to be imaged from a computed tomography (CT) detector. The method also includes reconstructing the acquired imaging data into an initial reconstruction image, and performing material characterization of an image volume of the initial reconstruction image to provide a re-mapped image volume. Further, the method includes performing forward projection on the re-mapped image volume to provide forward projection data, and providing an error projection based on the forward projection data. Also, the method includes filtering at least one of the initial reconstruction image, the re-mapped image volume, the forward projection data, or the error projection. The method also includes using the error projection to update the initial reconstruction image to provide an updated reconstruction image.

Abstract: Methods and systems are provided for boosting the contrast levels in an image reconstructed from projection data acquired at a single energy. In one embodiment, a method comprises modifying projection data corresponding to a material based on an absorption behavior of the material at a selected energy, wherein the projection data is acquired at an energy higher than the selected energy. In this way, contrast levels may be enhanced in an image reconstructed from projection data acquired at a typical single energy as though the image were reconstructed from projection data acquired at a lower energy.

Abstract: A method includes acquiring projection data of an object from a plurality of detector elements, reconstructing the acquired projection data into a first reconstructed image, and performing material characterization of an image volume of the first reconstructed image to reduce a number of materials analyzed in the image volume to two basis materials. Performing material characterization includes utilizing a generalized modeling function to estimate a fraction of at least one basis material within each voxel of the image volume. The method also includes generating a re-mapped image volume for the at least one basis material of the two basis materials, performing forward projection on at least the re-mapped image volume for the at least one basis material to produce a material-based projection, and generating multi-material corrected projections based on the material-based projection and a total projection attenuated by the object, which represents both of the two basis materials.

Abstract: Various methods and systems for dual energy spectral computed tomography imaging are provided. In one embodiment, a method for dual energy imaging comprises generating an image from a higher energy dataset and an updated lower energy dataset, wherein the updated lower energy dataset comprises a combination of a lower energy dataset and a pseudo projection dataset generated from the higher energy dataset. In this way, a weak low energy signal may be recovered, thereby enabling image reconstruction in spite of photon starvation and sparse views.

Abstract: A method includes acquiring projection data of an object from a plurality of detector elements, reconstructing the acquired projection data into a first reconstructed image, and performing material characterization of an image volume of the first reconstructed image to reduce a number of materials analyzed in the image volume to two basis materials. Performing material characterization includes utilizing a generalized modeling function to estimate a fraction of at least one basis material within each voxel of the image volume. The method also includes generating a re-mapped image volume for the at least one basis material of the two basis materials, performing forward projection on at least the re-mapped image volume for the at least one basis material to produce a material-based projection, and generating multi-material corrected projections based on the material-based projection and a total projection attenuated by the object, which represents both of the two basis materials.

Abstract: Various methods and systems for weighting material density images based on the material imaged are disclosed. In one embodiment, a method for dual energy imaging of a material comprises generating an odd material density image, generating an even material density image, applying a first weight to the odd material density image and a second weight to the even material density image, and generating a material density image based on a combination of the weighted odd material density image and the weighted even material density image. In this way, the image quality may be improved without increasing a radiation dosage.

Abstract: A method is provided including acquiring imaging data of an object to be imaged from a computed tomography (CT) detector. The method also includes reconstructing the acquired imaging data into an initial reconstruction image, and performing material characterization of an image volume of the initial reconstruction image to provide a re-mapped image volume. Further, the method includes performing forward projection on the re-mapped image volume to provide forward projection data, and providing an error projection based on the forward projection data. Also, the method includes filtering at least one of the initial reconstruction image, the re-mapped image volume, the forward projection data, or the error projection. The method also includes using the error projection to update the initial reconstruction image to provide an updated reconstruction image.