Toshiba Medical Systems Corporation

Kabushiki Kaisha Toshiba

Koninklijke Philips Corporation N.V.

University of California

Canon Medical Systems Corporation

University of Central Florida Research Foundation Inc

Accuray Inc.

Wenli Wang

Xiaofeng Niu

Daniel Gagnon

Hongwei Ye

Jian Zhou

Zhou Yu

Zhiqiang Hu

Evren Asma

Qiulin Tang

Jinyi Qi

Yun Dong

Calvin R Maurer

Satoru Nakanishi

Chuanyong Bai

Thomas Leroy Laurence

Alexander Katsevich

Wenyuan Qi

Zhicong Yu

Jacob D Shea

Zhengyan Wang

Amit Jain

Karthikayan Balakrishnan

Ting Xia

Christopher G Matthews

Guobao Wang

Ognian Ivanov

Yi Fan

Chong Zhang

An imaging apparatus and associated methods are provided to efficiently estimate scatter during multi-fraction treatments for improved quality and workflow. Estimated scatter from one fraction during a treatment course can be utilized during subsequent fractions, allowing for measurements with higher scatter-to-primary ratios. The quality of scatter estimates can be maintained, while workflow improves and dosage decreases. Scan configuration limits can be utilized to maintain a minimum level of scatter measurement quality. Patient information can be monitored to ensure that prior fraction scatter estimates are still applicable to current patient status.

Method and apparatus for image reconstruction and correction using inter-fractional information

An apparatus and method are provided for computed tomography (CT) imaging to reduce truncation artifacts due to a part of an imaged object being outside the scanner field of view (FOV) for at least some views of a CT scan. After initial determining extrapolation widths to extend the projection data to fill a truncation region, the extrapolation widths are combined into a padding map and smoothed to improve uniformity and remove jagged edges. Then a hybrid material model fits the measured projection data nearest the truncation region to extrapolate projection data filling the truncation region. Smoothing the padding map is improved by the insight that in general smaller extrapolation widths are more accurate and trustworthy. Further, practical applications often include multiple inhomogeneous materials. Thus, the hybrid material model provides a better approximation than single material models, and more accurate fitting is achieved.

Method and apparatus for projection domain truncation correction in computed-tomography (CT)

An apparatus and method of denoising a dynamic image is provided. The dynamic image can represent a time-series of snapshot images. The dynamic image is transformed, using a sparsifying transformation, into an aggregate image and a series of transform-domain images. The transform-domain images represent kinetic information of the dynamic images (i.e., differences between the snapshots), and the aggregate image represents static information (i.e., features and structure common among the snapshots). The transform-domain images, which can be approximated using a sparse approximation method, are denoised. The denoised transform-domain images are recombined with the aggregate image using an inverse sparsifying transformation to generate a denoised dynamic image. The transform-domain images can be denoised using at least one of a principal component analysis method and a K-SVD method.

Dynamic image denoising using a sparse representation

An embodiment provides a medical image processing apparatus that comprises circuitry. The circuitry obtains detection data representing detection events of radiation at a plurality of detector elements. The circuitry reconstructs an image by iteratively using an optimization-transfer algorithm to the detection data. The optimization-transfer algorithm uses a quadratic surrogate function that includes a curvature. The curvature is calculated using an inverse-background image.

Medical image processing apparatus and medical image diagnosis apparatus and medical image processing method

A method and apparatus is provided to iteratively reconstruct a computed tomography (CT) image using a hybrid pre-log and post-log iterative reconstruction method. A pre-log formulation is applied to values of the projection data that are less than a threshold (e.g., X-ray intensities corresponding to high absorption trajectories). The pre-log formulation has better noise modeling and better image quality for reconstructed images, but is slow to converge. Projection data values above the threshold are processed using a post-log formulation, which has fast convergence but poorer noise handling. However, the poorer noise handling has little effect on high value projection data. Thus, the hybrid pre-log and post-log method provides improved image quality by more accurately modeling the noise of low count projection data, without sacrificing the fast convergence of the post-log method, which is applied to high-count projection data.

Apparatus and method for hybrid pre-log and post-log iterative image reconstruction for computed tomography

A method of calculating a system matrix for time-of-flight (TOF) list-mode reconstruction of positron-emission tomography (PET) images, the method including determining a TOF geometric projection matrix G including effects of object attenuation; estimating an image-blurring matrix R in image space; obtaining a diagonal matrix D that includes TOF-based normalization factor; and calculating the system matrix H as H=DGR.

Image-based point-spread-function modelling in time-of-flight positron-emission-tomography iterative list-mode reconstruction

A method and apparatus is provided to iteratively reconstruct a PET image for emission data using separable quadratic surrogates (SQS). The quadratic surrogates include a Poisson likelihood surrogate that has a curvature that depends on a back-projection of an inverse of mean-background signal. The method can be used with Nesterov acceleration and ordered subsets to achieve quadratic convergence to an image minimizing a Poisson Likelihood objective function that includes a regularizer that penalizes roughness in the reconstructed image.

Fast, efficient, and list-mode compatible tomographic image reconstruction using a novel quadratic surrogate

A method and apparatus is provided to predict a regularization parameter for regularized iterative reconstruction of radiation detection data (e.g., computed tomography (CT) data or positron-emission tomography (PET) data) to generate a reconstructed image having specified statistical properties. The predicted regularization parameter is determined using a root-finding method performed on a transcendental objective function. The objective function is calculated using a three-dimensional Fourier transforms of an approximation to a shift invariant Hessian matrix and of matrix products between the forward-projection and back projection matrices of the system model and various (statistical) weight matrices. The specified statistical properties can include the standard deviation within a region of interest, a local spatial resolution, a low-contrast-detectability metric, etc. In addition to the specified statistical properties, the prediction of the regularization parameter accounts for the statistical properties of the radiation detection data, the display field of view, and the system model.

Apparatus and method of iterative image reconstruction using regularization-parameter control

A method and apparatus for generating crystal efficiency correction factors by performing a normalization calibration based on delayed data. The method and apparatus obtain delayed data from a scan of a patient using a Positron Emission Tomography (PET) scanner, generate a sinogram from the obtained delayed data, determine, using a processing circuit, mean fan and block line of response sensitivities from the generated sinogram, determine, using the processing circuit, mean detector efficiency based on the determined mean fan and block line of response sensitivities, determine, using the processing circuit, an individual crystal efficiency based on the determined mean fan and block line of response sensitivities and the mean detector efficiency for each module, and calculate the crystal efficiency correction factors based on the determined individual crystal efficiency of each module.

Method and system of random-event-based count-rate adaptive normalization for PET detector efficiency

An apparatus for performing a non-local means (NLM) filter is described. The pixel of the NLM-filtered image are weighted averages of pixels from a noisy image, where the weights are a measure of the similarity between patches of the noisy image. The similarity weights can be calculated using a Kullback-Leibler or a Euclidean distance measure. The similarity weights can be based on filtered patches of the noisy image. The similarity weights can be based on a similarity measure between patches of an anatomical image corresponding to the noisy image. The similarity weights can be calculated using a time series of noisy images to increase the statistical sample size of the patches. The similarity weights can be calculated using a weighted sum of channel similarity weights calculated between patches of noisy image that have been band-pass filtered. The NLM-filtered image can also be blended with a non-NLM-filtered image.

Apparatus and method for robust non-local means filtering of tomographic images

A method and system for determining a position of a source including obtaining prompt data and related delayed data from a Positron Emission Tomography (PET) scanner, generating a sinogram from the prompt data, generating crystal efficiency correction factors by performing a normalization calibration based on the obtained delayed data, performing normalization correction on the generated sinogram based on the crystal efficiency correction factors to generate a corrected sinogram, rebinning the corrected sinogram to generate a plurality of two-dimensional sinogram slices, and determining a central axis for each of the plurality of two-dimensional sinogram slices using a center estimation process.

Cylinder source software-positioning method for PET calibration and image quality assurance

A method and apparatus for reducing random events in positron emission tomography (PET) list mode data, the method including the steps of obtaining, for a PET scanner having a given reconstruction field of view (FOV), time-of-flight (TOF) prompt list-mode count data that includes TOF information, the TOF prompt list-mode count data including a plurality of entries; and filtering the obtained prompt list-mode count data by removing those entries in the obtained prompt list-mode count data that represent emission points lying outside a tangential TOF mask to obtain filtered list-mode count data.

Random coincidence reduction in positron emission tomography using tangential time-of-flight mask

A method is provided for estimating scatter in a positron emission tomography (PET) scan at multiple bed positions, the method comprising calculating a first scatter sinogram based on scatter data obtained at a first bed position, calculating a second scatter sinogram based on scatter data obtained at a second bed position, and deriving a third scatter sinogram for a third bed position between the first bed position and the second bed position, wherein the third scatter sinogram is derived from the first scatter sinogram according to a first percentage of overlap of the first bed position with the third bed position, and from the second scatter sinogram according to a second percentage of overlap of the second bed position with the third bed position.

Method and apparatus for estimating scatter in a positron emission tomography scan at multiple bed positions

A method of processing, by a processor of a computer, positron emission tomography (PET) information obtained from a PET detector, including the steps of obtaining a singles event list that includes a plurality of single event entries, each entry corresponding to a single event detected by the PET detector and including a timestamp, energy information, and crystal position information; and determining, based on the timestamp and the crystal position information of each entry and a predetermined coincidence time period, all event pairs within the plurality of single event entries, each event pair consisting of two single events whose respective timestamps differ by less than the predetermined coincidence time period, wherein the determining step determines that an event pair exists when at least two, but no more than k, single events are found within a given time window, wherein k is an integer value greater than or equal to two.

System for online/offline singles-pairing with keeping/rejecting multi-coincidences for positron emission tomography

A method of estimating random events in positron emission tomography list mode data, including obtaining time-of-flight (TOF) list mode count data that includes TOF information; converting the obtained TOF list mode count data into four-dimensional (4D) raw sinogram count data, without using the TOF information, wherein the 4D raw sinogram count data includes random count values; interpolating the 4D raw sinogram count data to generate 4D interpolated sinogram count data; low-pass filtering the 4D interpolated sinogram count data to remove noise; converting the low-pass filtered 4D interpolated sinogram count data into filtered 4D raw sinogram count data; and generating, by a processor, five-dimensional (5D) TOF raw sinogram count data from the filtered 4D raw sinogram count data by effectively applying a TOF mask filter to the filtered 4D raw sinogram count data.

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Wenli Wang