Toshiba Medical Systems Corporation

Kabushiki Kaisha Toshiba

University of Chicago

Yu Zou

Xiaolan Wang

Yuexing Zhang

Adam Petschke

Zhou Yu

Daniel Gagnon

Michael D Silver

Chunguang Cao

Alexander A Zamyatin

Miesher Rodrigues

Xiaochuan Pan

Daxin Shi

Maryellen L Giger

Lifeng Yu

Howard J Halpern

Chien-min Kao

Emil Sidky

Dan Xia

Charles A Pelizzari

Martin King

Seungryong Cho

Zhi Yang

Zhengyan Wang

Gin-Chung Wang

Kozo Sato

Satoru Ohishi

Satoru Nakanishi

Hiroaki Miyazaki

Ilmar A Hein

Naruomi Akino

Gin Chung Wang

Yujie Lu

Richard Thompson

Aleksandr Zamyatin

Be-Shan Chiang

Thomas Labno

Sachin S Junnarkar

Sachin Moghe

Alan Karr

Dan Xu

Alex Zamyatin

Mike Silver

Anusha Muthu Natarajan

Ilmar Hein

A method and apparatus is provided to decompose spectral computed tomography (CT) projection data into material components using singles-counts and total-counts projection data. The singles-counts projection data more accurately solves the material decomposition problem, but can produce multiple results only one of which is correct. The total-counts projection data generates a unique result, but is less precise. The total-counts projection data is used to disambiguate the multiple results of the singles-counts projection data providing a unique results that is also precise. The unique and precise material decomposition can be achieved by limiting a search region for the singles-counts result to a neighborhood surrounding the total-counts result, choosing a singles-counts result that is closest to the total-counts result, choosing a singles-counts result that minimizes a total-counts cost function, or using a combined cost function that includes a singles-counts projection data and energy-integrated projection data.

Apparatus and method for material decomposition of spectrally resolved projection data using singles counts

A method and apparatus is provided to calculate scatter using a method to determine primary X-ray flux, first-scatter flux, and multiple-scatter flux using an integral formulation of a radiative transfer equation and using spherical-harmonic expansion. The integral for the primary X-ray flux does not include a spherical-harmonic expansion. The integral for the first-scatter flux includes an angle-dependent scatter cross-section. The integral for the multiple-scatter flux is performed iteratively, includes spherical harmonics, and includes a scatter cross-section expanded using Legendre polynomials. The integrals of attenuation along propagation rays can be accelerated using material decomposition of the attenuation coefficients. An anti-scatter-grid term can be included in the integrals to account for the effects of an anti-scatter grid on the fluxes prior to detection of the X-rays.

Scatter simulation with a radiative transfer equation using direct integral spherical harmonics method for computed tomography

A computed tomography (CT) method and apparatus including a radiation source configured to produce radiation directed to an object space, and a plurality of detector elements configured to detect the radiation produced from the radiation source through the object space and generate projection data. A rotation mount is configured to rotate the radiation source around the object space. Processing circuitry is configured to cause the rotation mount to rotate the radiation source, and to receive the projection data. The projection data includes a plurality of projection data sets. The processing circuitry calculates a set of weights based on the projection data sets, calculates a set of pre-weights based on the weights, and minimizes a penalized weighted least-squares cost function to produce a reconstructed image. The cost function is a sum of a weighted least-squares term, weighted using the weights, and a penalty term weighted using the pre-weights.

Computed tomography apparatus and empirical pre-weighting method for decreasing image noise nonuniformity

An apparatus and method of processing X-ray projection data including spectral computed tomography (CT) projection data. The spectral CT data is decomposed into material projection lengths using a material-decomposition method that includes an initial-estimate method to provide an initial projection-lengths estimate. The initial-estimate method can include first reconstructing an image using non-spectral CT data, and then subdividing the reconstructed image into materials according to the relative attenuation density of areas within the reconstructed image (e.g., high attenuation areas correspond to a high attenuation material such as bone). The projection length estimates of each material are then obtained by forward projecting the corresponding subdivision of the reconstructed image. Also, the initial estimate can be obtained/refined by selecting the projection lengths with smallest cost-function value from randomly chosen projection lengths within a sample space. The initial estimate can also be conditioned on the X-ray flux at the X-ray source.

More efficient method and apparatus for detector response correction and material decomposition of projection data obtained using photon-counting detectors

An apparatus and a method are provided for calculating an output spectrum of a photon-counting detector based on an incident spectrum. The apparatus includes processing circuitry to determine a plane extending from a top face of the photon-counting detector that includes regions that all possible incident rays will transverse; divide the determined plane into subregions; calculate a detector response function for each of the subregions; determine an overall detector response function by summing the calculated detector response function for each of the subregions and normalizing the summation by an area of the determined plane; and calculate the output spectrum based on the overall detector response function and the incident spectrum.

Polar effect model, system, and method for photon counting detector in medical imaging systems including computed tomography

A computed tomography (CT) imaging apparatus includes a radiation source configured to emit X-rays; a plurality of photon-counting detectors configured to detect X-rays emitted by the radiation source and generate a photon counting signal based on the detected X-rays; and processing circuitry to obtain a kV-waveform used by the radiation source to generate the X-rays during a scan of an object, and adjust at least one energy threshold dividing the photon counting signal into a plurality of spectra bins in accordance with the obtained kV-waveform.

Wide X-ray spectrum photon counting computed tomography

A method and apparatus for estimating a parameter vector including a plurality of parameters of a detector response model of a photon-counting detector. The method includes calculating a modeled spectrum based on an input spectrum and an initial value of the plurality of parameters. For each detector, a difference between the normalized photon count of the measured spectrum and the normalized modeled spectrum is calculated. A root mean square error (RMSE) between the measured and modeled spectra is obtained by squaring the normalized difference and weighting the normalized difference by a weighting factor. The parameter vector is updated until an optimum RMSE value is achieved. Upon determining optimal values of the parameter vector, measured data that is obtained via a patient scan is corrected based on the optimal parameter vector.

Count-weighted least squares parameter estimation for a photon-counting detector

A method and apparatus is provided to reconstruct a collective image of a multiple method/geometry imaging system (e.g., a hybrid computed tomography system having energy-integrating detectors arranged in a third-generation geometry and photon-counting detectors arranged in a fourth generation geometry), wherein a splitting-based iterative algorithm using modified dual variables is used in the image reconstruction. Whereas a separate image for each method/geometry of the multiple method/geometry imaging system can be obtained by solving the distinct system-matrix equation corresponding to each respective method/geometry, the collective image is obtained by simultaneously solving a collective optimization problem including all respective system-matrix. The collective image is obtained more efficiently using variable splitting to subdivide the optimization into subproblems that are solved in an iterative fashion. For some applications, the collective image can be further improved by including a beam-hardening correction step.

Computed tomography using simultaneous image reconstruction with measurements having multiple distinct system matrices

A computed tomography (CT) apparatus and a method for identifying photon-counting detectors that are polarized due to high flux, thereby rendering the photon-counting detector inoperable. The data obtained from the photon-counting detectors that are determined to be polarized is skipped during an image pre-reconstruction phase. The data is further assigned a weight of zero during an image reconstruction phase in order to avoid imaging artifacts in the reconstructed CT image.

Method for identifying and processing detector polarization in photon-counting spectral X-ray detectors

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.

Method and system for spectral computed tomography (CT) with inner ring geometry

An apparatus is provided that includes a digital processing circuit to obtain a digital signal corresponding to an output signal of a photon-counting detector; determine, from the obtained digital signal, a plurality of X-ray photons received by the photon-counting detector during a measurement period; determine a corresponding energy level of each of the plurality of X-ray photons; determine, based on the corresponding energy level, a corresponding weight for each of the plurality of X-ray photons; and calculate a sum of the corresponding weights of the plurality of X-ray photons.

Energy-weighted single-binning for a photon-counting detector

An apparatus and method of processing X-ray projection data obtained using photon-counting detectors and having multiple spectral components. The processing of the projection data includes correcting for nonlinear detector response, where the detector response model includes: pileup, ballistic deficit effects, polar effects, and characteristic X-ray escape. The processing of the projection data also includes a material decomposition mapping the projection data from spectral components into material components corresponding to high-Z and low-Z materials. The material decomposition includes a noise balancing process where the allocation of spectral components between a high-energy and a low-energy combination of spectral components is adjusted such that both high- and low-energy components have signal-to-noise ratios of similar magnitude. For computed tomography (CT) applications, material decomposition can be followed by image reconstruction and then image post-processing and presentation. For non-CT applications, material decomposition can be followed by image post-processing and presentation.

Pre-reconstruction calibration, data correction, and material decomposition method and apparatus for photon-counting spectrally-resolving X-ray detectors and X-ray imaging

A method and apparatus of aligning calibration projection data with object projection data to improve calibration corrections of the object projection data. In a first implementation, the method interpolates and upsamples both the calibration and object data, then shifts the upsampled calibration data to match a sub-view angular offset of the object data, and then performs calibration corrections before down-sampling the corrected object data. In a second implementation, the method continuously scans an object space&#x2014;with the object absent (present) in the object space&#x2014;to obtain calibration data (object absent) and object data (object present) both having the same sub-view angular offset. In a third implementation, the method obtains multiple scans having different sub-view angular offsets, organizes the scans into bins according to their respective sub-view angular offsets, and chooses the appropriate sub-view angular offsets bin for calibration corrections of the object data.

Computed tomography scanner calibration with angle correction for scan angle offset

A detector includes a photon-counting detector (PCD) layer and a cathode layer arranged adjacent to the PCD layer. The detector further includes a plurality of pixilated anodes arranged adjacent to the photon-counting detecting layer on a side opposite to the cathode layer. The detector also includes a plurality of collimator segments arranged above the cathode layer so as to block a portion of X-ray photons emitted from an X-ray source from reaching the anodes, where each collimator segment is arranged above a portion of at least one anode.

Apparatus and method for collimating X-rays in spectral computer tomography imaging

A CT scanner apparatus includes an X-ray source mounted on a gantry of the CT scanner apparatus. The CT scanner apparatus also includes a first X-ray detector mounted on the gantry opposite to the X-ray source, and configured to detect X-rays emitted from the X-ray source and transmitted through an object. The CT scanner apparatus also includes a fixed, sparse array of second X-ray detectors. Each of the second X-ray detectors includes a plurality of stacked scintillators and a photosensor adjacent to a sidewall of the stacked scintillators in a side-readout configuration.

Multiple-layered energy-integrating detector in a hybrid computed tomography scanner

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Naperville, IL, United States of America

Yu Zou