Abstract: Provided are a tomography apparatus and a method for reconstructing a tomography image. The method includes obtaining a plurality of raw data corresponding to a plurality of views by performing a tomography scan on an object and deblurring each of the plurality of raw data based on a point spread function (PSF) that varies according to locations in a field of view (FOV) in a gantry. The method also includes reconstructing a final tomography image in which a motion of the object is corrected from the plurality of deblurred raw data based on a motion vector indicating the motion of the object.

Abstract: A method of computing statistical weights for a computed tomography (CT) iterative reconstruction process is provided. The method includes obtaining detector count data from a CT scan of an object; calculating variance data based on the count data and an electronic noise variance; transforming the calculated variance data to obtain statistical weight data; and performing the CT iterative reconstruction process using the statistical weight data and raw projection data to obtain a reconstructed CT image.

Abstract: A system and method for generating X-rays are disclosed. The method may include emitting an electron beam from a cathode to a focal track of a rotating target. The method may further include deflecting the electron beam onto a first region of the focal track at a first time, and deflecting the electron beam onto a second region of the focal track at a second time. The first region of the focal track may be separated from the second region of the focal track. The method may further include generating X-rays in response to the electron beam deflected onto the first region of the focal track or onto the second region of the focal track.

Abstract: Photon counting detectors are sparsely placed at predetermined positions in the fourth-generation geometry around an object to be scanned in spectral Computer Tomography (CT). An X-ray emitting source rotates radially outside the sparsely placed photon counting detectors. Furthermore, the integrating detectors are placed in the third-generation in combination to the sparsely placed photon counting detectors at predetermined positions in the fourth-generation geometry.

Abstract: Provided are a tomography apparatus and a method for reconstructing a tomography image. The method includes obtaining a plurality of raw data corresponding to a plurality of views by performing a tomography scan on an object and deblurring each of the plurality of raw data based on a point spread function (PSF) that varies according to locations in a field of view (FOV) in a gantry. The method also includes reconstructing a final tomography image in which a motion of the object is corrected from the plurality of deblurred raw data based on a motion vector indicating the motion of the object.

Abstract: Cone beam artifacts arise in circular CT reconstruction. The cone beam artifacts are substantially removed by reconstructing a reference image from measured data at circular source trajectory, generating synthetic data by forward projection of the reference image along a pre-determined source trajectory, which supplements the circular source trajectory to a theoretically complete trajectory, reconstructing a correction image from the synthetic data and applying a scaling factor whose value is adaptively determined and optimized based upon the minimization of a predetermined cone beam artifact metric. Ultimately, the cone beam artifact is substantially reduced by generating a corrected image using the reference image and the correction image that has been optimally scaled based upon the adaptively determined scaling factor value.

Abstract: Cone beam artifacts arise in circular CT reconstruction. The cone beam artifacts are substantially removed by reconstructing a reference image from measured data at circular source trajectory, differentiating the reference image; generating synthetic data by forward projection of the differentiated reference image along a pre-determined source trajectory, which supplements the circular source trajectory to a theoretically complete trajectory, reconstructing a correction image from the synthetic data and optionally applying a scaling factor. Ultimately, the cone beam artifact is substantially reduced by generating a corrected image using the reference image and the correction image that has been optimally scaled based upon the adaptively determined scaling factor value.

Abstract: A CT imaging apparatus has processing circuitry that is configured to obtain projection data collected by a CT detector during a scan of an object. The processing circuitry is also configured to perform iterative reconstruction of the projection data to generate a current image. The iterative reconstruction includes filtering forward-projected data during backprojection or filtering image data prior to forward projection to model system optics. The processing circuitry is also configured to combine the current image with a previously-obtained image to generate an updated image.

Abstract: Cone beam artifacts arise in circular CT reconstruction. The cone beam artifacts are substantially removed by reconstructing a reference image from measured data at circular source trajectory, differentiating the reference image; generating synthetic data by forward projection of the differentiated reference image along a pre-determined source trajectory, which supplements the circular source trajectory to a theoretically complete trajectory, reconstructing a correction image from the synthetic data and optionally applying a scaling factor. Ultimately, the cone beam artifact is substantially reduced by generating a corrected image using the reference image and the correction image that has been optimally scaled based upon the adaptively determined scaling factor value.

Abstract: A medical imaging apparatus, processing device or specialized circuit can include an input interface to input scan data of a medical image scan of a target object, a processor to generate an output image from the input scan data, and an output interface to output the output image to, e.g., a display. The processor can execute a first reconstruction of the scan data to obtain an intermediate image of the target object, a high-density forward projection of the intermediate object to obtain generated data, a sinogram updating using both of the generated data and the scan data to obtain a high-resolution sinogram, and a second reconstruction based on the high-resolution sinogram to obtain an output image.

Abstract: Cone beam artifacts arise in circular CT reconstruction. The cone beam artifacts are substantially removed by reconstructing a reference image from measured data at circular source trajectory, generating synthetic data by forward projection of the reference image along a pre-determined source trajectory, which supplements the circular source trajectory to a theoretically complete trajectory, reconstructing a correction image from the synthetic data and applying a scaling factor whose value is adaptively determined and optimized based upon the minimization of a predetermined cone beam artifact metric. Ultimately, the cone beam artifact is substantially reduced by generating a corrected image using the reference image and the correction image that has been optimally scaled based upon the adaptively determined scaling factor value.

Abstract: Iterative reconstruction (IR) algorithms are advantageous over standard filtered backprojection (FBP) algorithms by improving resolution and noise performance. In this regard, model-based IR algorithms (MBIR) have been developed to incorporate accurate system models into IR and result in a better image quality than IR algorithms without a system model. System optics are included in both forward and backprojection (IRSOM-FPBP).

Abstract: Photon counting detectors are sparsely placed at predetermined positions in the fourth-generation geometry around an object to be scanned in spectral Computer Tomography (CT). An X-ray emitting source rotates radially outside the sparsely placed photon counting detectors. Furthermore, the integrating detectors are placed in the third-generation in combination to the sparsely placed photon counting detectors at predetermined positions in the fourth-generation geometry.

Abstract: A method of computing statistical weights for a computed tomography (CT) iterative reconstruction process is provided. The method includes obtaining detector count data from a CT scan of an object; calculating variance data based on the count data and an electronic noise variance; transforming the calculated variance data to obtain statistical weight data; and performing the CT iterative reconstruction process using the statistical weight data and raw projection data to obtain a reconstructed CT image.

Abstract: The methods and systems of the present invention is an algorithm which estimates motion inside objects that change during the scan. The algorithm is flexible and can be used for solving the misalignment correction problem and, more generally, for finding scan parameters that are not accurately known. The algorithm is based on Local Tomography so it is faster and is not limited to a source trajectory for which accurate and efficient inversion formulas exist.

Abstract: Photon starvation causes streaks and noise and seriously impairs the diagnostic value of the CT imaging. To reduce streaks and noise, a new scheme of adaptive Gaussian filtering relies on the diffusion-derived scale-space concept in one embodiment of the current invention. In scale-space view, filtering by Gaussians of different sizes is similar to decompose the data into a sequence of scales. As the scale measure, the variance of the filter linearly relates to the noise standard deviation of a predetermined noise model in the new filtering method. The new filter has only one optional parameter that remains stable once tuned. Although single-pass processing using the new filter generally achieves desired results, iterations are optionally performed.

Abstract: A medical imaging apparatus, processing device or specialized circuit can include an input interface to input scan data of a medical image scan of a target object, a processor to generate an output image from the input scan data, and an output interface to output the output image to, e.g., a display. The processor can execute a first reconstruction of the scan data to obtain an intermediate image of the target object, a high-density forward projection of the intermediate object to obtain generated data, a sinogram updating using both of the generated data and the scan data to obtain a high-resolution sinogram, and a second reconstruction based on the high-resolution sinogram to obtain an output image.

Abstract: The CT imaging system optimizes its image generation by updating an image with the current application of a data fidelity update and a regularization update together in a single step in an iterative reconstruction algorithm. The iterative reconstruction algorithm includes the ordered subsets simultaneous algebraic reconstruction technique (OSSART) and the simultaneous algebraic reconstruction technique (SART). The data fidelity update and the regularization update are independently obtained using some predetermined statistical information such as noise and or error in matching the real data.

Abstract: Spatial resolution is substantially improved by simulating a system blur kernel including an angle variable in the forward projection during a predetermined iterative reconstruction technique. The iterative reconstruction acts as a deconvolution, which overcomes certain restrictions of system optics. In general, resolution is substantially improved with cone beam and helical data without a large increase in noise.

Abstract: Iterative reconstruction (IR) algorithms are advantageous over standard filtered backprojection (FBP) algorithms by improving resolution and noise performance. In this regard, model-based IR algorithms (MBIR) have been developed to incorporate accurate system models into IR and result in a better image quality than IR algorithms without a system model. System optics are included in both forward and backprojection (IR-SOM-FPBP).