Abstract: The present disclosure discloses a CANopen-based data transmission gateway changeover method, system and apparatus.

Abstract: According to one embodiment, a photon-counting detector (PCD) includes a plurality of macro-pixels. The plurality of macro-pixels arranged on a semiconductor crystal has a first face and a second face. The first face and the second face are parallel. Each macro-pixel from the plurality of macro-pixels is configured to acquire projection data for generating a reconstructed image. The plurality of macro-pixels each includes at least one large micro-pixel is disposed within the each macro-pixel and at least two small micro-pixels is disposed within the each macro-pixel. Each of the at least two small micro-pixels has a surface area that is less than a surface area of the at least one large micro-pixel.

Abstract: An apparatus and method are described using a forward model to correct pulse pileup in spectrally resolved X-ray projection data from photon-counting detectors (PCDs). The forward model represents pulse pileup effects using an integral in which the integrand includes a term that is a function of a count rate, which term is called a spectrum distortion correction function. This correction function can be represented as superposition of basis energy functions and corresponding polynomials of the count rate, which are defined by the polynomial coefficients. To calibrate the forward model, the polynomial coefficients are adjusted to optimize an objective function, which uses calibration data having known projections lengths for the material components of a material decomposition. To determine projection lengths for projection data from a computed tomography scan, the calibrated polynomial coefficients are held constant and the projection lengths are adjusted to optimize an objective function.

Abstract: An apparatus and method are described using a forward model to correct pulse pileup in spectrally resolved X-ray projection data from photon-counting detectors (PCDs). The forward model represents pulse pileup effects using an integral in which the integrand includes a term that is a function of a count rate, which term is called a spectrum distortion correction function. This correction function can be represented as superposition of basis energy functions and corresponding polynomials of the count rate, which are defined by the polynomial coefficients. To calibrate the forward model, the polynomial coefficients are adjusted to optimize an objective function, which uses calibration data having known projections lengths for the material components of a material decomposition. To determine projection lengths for projection data from a computed tomography scan, the calibrated polynomial coefficients are held constant and the projection lengths are adjusted to optimize an objective function.

Abstract: A method and apparatuses are provided to estimate, for two or more detector elements in an array of photon-counting detector elements, respective energy spectra of an X-ray beam incident on the corresponding detector elements from an X-ray source, the energy spectra being estimated by modeling X-ray attenuation as a function of X-ray energy when an X-ray beam is transmitted through a filter and set, for each detector element of the two or more detector elements, a first energy threshold of an energy range that is detected by the each detector element, the first energy threshold of the each detector element being based on the estimated energy spectra of the each detector element.

Abstract: A method and apparatuses are provided to estimate, for two or more detector elements in an array of photon-counting detector elements, respective energy spectra of an X-ray beam incident on the corresponding detector elements from an X-ray source, the energy spectra being estimated by modeling X-ray attenuation as a function of X-ray energy when an X-ray beam is transmitted through a filter and set, for each detector element of the two or more detector elements, a first energy threshold of an energy range that is detected by the each detector element, the first energy threshold of the each detector element being based on the estimated energy spectra of the each detector element.

Abstract: A method and apparatuses are provided to identify and correct partial volume errors (PVEs) in material decomposition of a spectral computed tomography (CT) scan, due to different X-ray trajectories incident on a same macro-pixel passing through different material components (e.g., bone and water). Macro-pixels are virtual crystals generated by aggregating the signals/counts from several smaller actual pixels (i.e., micro-pixels) of a detector array. Thus, when a PVE is identified within a macro-pixel, the separate signals/counts from the micro-pixels can be used for material decomposition, instead of the aggregated signals/counts of the macro-pixel, thereby providing improved spatial resolution of the material components and, at least partial, overcoming the PVE. A measure of the difference between spectrally-resolved counts based a material projection lengths (e.g., from a calibrated lookup table) and the measured counts of the macro-pixel can be used to identify PVEs, e.g.

Abstract: A method and apparatuses are provided to identify and correct partial volume errors (PVEs) in material decomposition of a spectral computed tomography (CT) scan, due to different X-ray trajectories incident on a same macro-pixel passing through different material components (e.g., bone and water). Macro-pixels are virtual crystals generated by aggregating the signals/counts from several smaller actual pixels (i.e., micro-pixels) of a detector array. Thus, when a PVE is identified within a macro-pixel, the separate signals/counts from the micro-pixels can be used for material decomposition, instead of the aggregated signals/counts of the macro-pixel, thereby providing improved spatial resolution of the material components and, at least partial, overcoming the PVE. A measure of the difference between spectrally-resolved counts based a material projection lengths (e.g., from a calibrated lookup table) and the measured counts of the macro-pixel can be used to identify PVEs, e.g.

Abstract: A method and apparatus is provided to simulate and correct for scatter flux detected in a computed tomography (CT) scanner. The scatter flux from a bowtie filter and an anti-scatter grid are pre-calculated to generate respective scatter tables. Scatter from an imaged object is simulated for some views of a CT scan using a three-step radiative transfer equation (RTE) method. Using the simulated scatter flux from these views, an accelerated simulation method, such as a multiplicative method, an additive method, and a kernel-based method, can determine scatter flux for the remaining views. The spatial model for X-ray scatter from the object can be based on a reconstructed image of object, and can be segmented into organs and material components having different scatter cross-sections. A scatter model outside the imaging region can be extrapolated using low-dose scanning, a scout scan, and/or anatomical information.

Abstract: According to one embodiment, a photon-counting detector (PCD) includes a plurality of macro-pixels. The plurality of macro-pixels arranged on a semiconductor crystal has a first face and a second face. The first face and the second face are parallel. Each macro-pixel from the plurality of macro-pixels is configured to acquire projection data for generating a reconstructed image. The plurality of macro-pixels each includes at least one large micro-pixel is disposed within the each macro-pixel and at least two small micro-pixels is disposed within the each macro-pixel. Each of the at least two small micro-pixels has a surface area that is less than a surface area of the at least one large micro-pixel.

Abstract: A method and apparatus is provided to simulate and correct for scatter flux detected in a computed tomography (CT) scanner. The scatter flux from a bowtie filter and an anti-scatter grid are pre-calculated to generate respective scatter tables. Scatter from an imaged object is simulated for some views of a CT scan using a three-step radiative transfer equation (RTE) method. Using the simulated scatter flux from these views, an accelerated simulation method, such as a multiplicative method, an additive method, and a kernel-based method, can determine scatter flux for the remaining views. The spatial model for X-ray scatter from the object can be based on a reconstructed image of object, and can be segmented into organs and material components having different scatter cross-sections. A scatter model outside the imaging region can be extrapolated using low-dose scanning, a scout scan, and/or anatomical information.