Abstract:
A technique for acquiring desired image data in an imaging system comprising at least one radiation source and a detector is described. Initially, preliminary image data corresponding to an object may be acquired. Further, at least one parameter associated with the radiation source and corresponding to a particular view angle of the radiation source may be determined based on the preliminary image data and a priori information. Similarly, at least one parameter associated with the detector and corresponding to the particular view angle may be determined based on a priori information and the preliminary image data. Efficient operating modes of the radiation source and the detector corresponding to the particular view angle may be selected based on the determined parameters to achieve a desired system performance. Subsequently, the final image data may be acquired using the selected operating modes of the radiation source and the detector.
Abstract:
A method for scanning a stream of objects includes conveying the stream of objects through a scanning system using a conveyor, marking a leading edge position of an object within the stream of objects with respect to a first known distance between a sensor and a start of a scan range, and recording data associated with the object when the leading edge position reaches the start of the scan range. The method also includes marking a trailing edge position of the object with respect to a second known distance between the sensor and an end of the scan range, halting recording of the data when the trailing edge reaches the end of the scan range, and generating a three-dimensional image of the object based on the recorded data.
Abstract:
A new method extends iterated coordinate descent (“ICD”)—an optimization method employed in some statistical reconstruction algorithms—to handle material decomposition (“MD”) for energy discriminating computed tomography (“EDCT”) acquisitions.
Abstract:
A method for reconstructing cone-beam projection data is provided. The method comprises scanning an object in helical mode, wherein the scanning comprises obtaining cone-beam projection data. The method further comprises processing the cone-beam projection data along a plurality of data filtering curves. The processing includes processing the cone-beam projection data along a portion of the data filtering curves that extends outside of a physical detector area to a virtual detector area. Then, the method comprises using the processed cone-beam projection data in the generation of a reconstructed image of the object.
Abstract:
A method for reconstructing image data from acquired tomographic projection data measurements is provided. The projection data measurements comprise one or more missing data measurements. The method comprises generating a coarse-resolution projection data set from the acquired projection data measurements and performing an iterative reconstruction on the coarse-resolution projection data set to generate a coarse-resolution reconstructed data set. Then, the method comprises reprojecting the coarse-resolution reconstructed data set to obtain one or more estimates for the one or more missing data measurements. The one or more estimated missing data measurements are then recombined with the acquired projection data measurements, to generate a recombined data set. Then, a direct reconstruction algorithm is applied to the recombined data set to generate the reconstructed image data.
Abstract:
Systems and methods are provided for acquiring and reconstructing projection data using a computed tomography (CT) system having stationary distributed X-ray sources and detector arrays. In one embodiment, a non-sequential activation of X-ray source locations on an annular source is employed to acquire projection data. In another embodiment, a distributed source is tilted relative to an axis of the scanner to acquire the projection data. In a further embodiment, a plurality of X-ray source locations on an annular source are activated such that the aggregated signals correspond to two or more sets of spatially interleaved helical scan data.
Abstract:
Systems and methods are provided for acquiring and reconstructing projection data that is mathematically complete or sufficient using a computed tomography (CT) system having stationary distributed X-ray sources and detector arrays. In one embodiment, a distributed source is provided as arcuate segments offset in the X-Y plane and along the Z-axis.
Abstract:
Methods are provided for iteratively reconstructing an image signal to generate a reconstructed image signal. In one embodiment, sub-iterations of each iteration are performed on pixel subsets. The pixel subsets may be composed of pixels neighboring or spatially separated pixel. In a further embodiment, each iteration is performed at a different resolution. Systems and computer routines for processing image data iteratively in accordance with these techniques are also provided.
Abstract:
A computed tomography (CT) reconstruction method includes implementing an iterative image reconstruction process for CT metrology of an object, wherein the iterative reconstruction process utilizes accurate forward projection. During each of a plurality of iterations, a reconstructed image is constrained by utilizing prior outer edge information obtained from a modality in addition to CT, and then transformed to a projection domain so as to generate a calculated sinogram. A correction image is determined based on the calculated sinogram and a measured sinogram.
Abstract:
A method for computing volumetric perfusion in a spatially stationary organ using a computed tomography (CT) imaging system includes positioning an area detector such that the area detector encompasses a spatially stationary organ within the field of view of the imaging system for all view angles, operating the CT imaging system in a cine mode to acquire a plurality of projection data representative of the tissue dynamics in the spatially stationary organ, processing the projection data, temporally filtering respective signals from volume elements of the reconstructions of the projection data which are representative of the tissue dynamics and computing the volumetric perfusion in the organ using the temporally filtered signals from volume elements.