Abstract: The present disclosure provides systems and methods for performing quality control assessments of a three dimensional (3D) printing system. In particular, the present disclosure provides a phantom designs for use in 3D printing systems, as well as methods of quality control for a 3D printing system performed using a 3D printed phantom.

Abstract: Described here are systems and methods for optimization techniques for automatically selecting x-ray beam spectra, energy threshold, energy bin settings, and other imaging technique parameters for photon-counting detector computed tomography (“PCCT”). The techniques described here are generally based on subject or object size, material of interest, and location of the target material. Advantageously, the optimizations can be integrated with different PCCT systems to automatically select optimal imaging technique parameters before scanning a particular subject or object.

Abstract: A method for creating an energy series of images acquired using a multi-energy computed tomography (CT) imaging system having a plurality of energy bins includes acquiring, with the multi-energy CT imaging system, a series of energy data sets, where each energy data set is associated with at least one of the energy bins. The method includes producing a conglomerate image using at least a plurality of the energy data sets and, using the conglomerate image, reconstructing an energy series of images, each image in the energy series of images corresponding to at least one of the energy data sets.

Abstract: A method for creating an energy series of images acquired using a multi-energy computed tomography (CT) imaging system having a plurality of energy bins includes acquiring, with the multi-energy CT imaging system, a series of energy data sets, where each energy data set is associated with at least one of the energy bins. The method includes producing a conglomerate image using at least a plurality of the energy data sets and, using the conglomerate image, reconstructing an energy series of images, each image in the energy series of images corresponding to at least one of the energy data sets.

Abstract: A method for creating an energy series of images acquired using a multi-energy computed tomography (CT) imaging system having a plurality of energy bins includes acquiring, with the multi-energy CT imaging system, a series of energy data sets, where each energy data set is associated with at least one of the energy bins. The method includes producing a conglomerate image using at least a plurality of the energy data sets and, using the conglomerate image, reconstructing an energy series of images, each image in the energy series of images corresponding to at least one of the energy data sets.

Abstract: A method for creating an energy series of images acquired using a multi-energy computed tomography (CT) imaging system having a plurality of energy bins includes acquiring, with the multi-energy CT imaging system, a series of energy data sets, where each energy data set is associated with at least one of the energy bins. The method includes producing a conglomerate image using at least a plurality of the energy data sets and, using the conglomerate image, reconstructing an energy series of images, each image in the energy series of images corresponding to at least one of the energy data sets.

Abstract: A system and method for reducing image noise and artifacts in coronary computed tomography angiography includes acquisition of CT images at multiplicity of CT slices arranged in such a fashion throughout the phases of the cardiac cycle as to utilize the majority of the X-ray radiation to which the myocardium exposed during the cycle. The acquired imaging data is processed with the use of a TAF filter to reduce the amount of noise and artifacts associated with the CT's system operating at low tube current. The TAF filter is configured to adapt the filtering strength in time domain according to temporal variations of the same anatomical location as identified in its corresponding CT slices.

Abstract: Methods, systems, and apparatuses for non-convex prior image constrained compressed sensing are disclosed. In one embodiment, a method is provided for iterative image reconstruction for medical imaging applications which employ a prior image to constrain the reconstruction process allowing the use of fewer high SNR samples or complete but lower SNR samples. The objective function made use of non-convex compressed sensing methods during the iterative reconstruction process. Applications include, but are not limited to radiation dose reduction and fast image acquisition.

Abstract: A system and method for reducing image noise and artifacts in coronary computed tomography angiography includes acquisition of CT images at multiplicity of CT slices arranged in such a fashion throughout the phases of the cardiac cycle as to utilize the majority of the X-ray radiation to which the myocardium exposed during the cycle. The acquired imaging data is processed with the use of a TAF filter to reduce the amount of noise and artifacts associated with the CT's system operating at low tube current. The TAF filter is configured to adapt the filtering strength in time domain according to temporal variations of the same anatomical location as identified in its corresponding CT slices.

Abstract: A method for creating an energy series of images acquired using a multi-energy computed tomography (CT) imaging system having a plurality of energy bins includes acquiring, with the multi-energy CT imaging system, a series of energy data sets, where each energy data set is associated with at least one of the energy bins. The method includes producing a conglomerate image using at least a plurality of the energy data sets and, using the conglomerate image, reconstructing an energy series of images, each image in the energy series of images corresponding to at least one of the energy data sets.

Abstract: An image reconstruction method applicable to a number of different imaging modalities including magnetic resonance imaging (MRI), x-ray computed tomography (CT), positron emission tomography (PET), and single photon emission computed tomography (SPECT) is disclosed. A sparsifying image is reconstructed from a series of acquired undersampled data to provide a priori knowledge of a subject being imaged. An iterative reconstruction process is further employed to iteratively determine a correction image for a given image frame that, when subtracted from the sparsifying image, produces a quality image for the image frame.

Abstract: Methods, systems, and apparatuses for non-convex prior image constrained compressed sensing are disclosed. In one embodiment, a method is provided for iterative image reconstruction for medical imaging applications which employ a prior image to constrain the reconstruction process allowing the use of fewer high SNR samples or complete but lower SNR samples. The objective function made use of non-convex compressed sensing methods during the iterative reconstruction process. Applications include, but are not limited to radiation dose reduction and fast image acquisition.

Abstract: An image reconstruction method applicable to a number of different imaging modalities including magnetic resonance imaging (MRI), x-ray computed tomography (CT), positron emission tomography (PET), and single photon emission computed tomography (SPECT) is disclosed. A sparsifying image is reconstructed from a series of acquired undersampled data to provide a priori knowledge of a subject being imaged. An iterative reconstruction process is further employed to iteratively determine a correction image for a given image frame that, when subtracted from the sparsifying image, produces a quality image for the image frame.