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1.发明申请公开(公告)号：US20220088417A1
公开(公告)日：2022-03-24
申请号：US17545030
申请日：2021-12-08
摘要： The present invention is directed to multiple aperture devices (MADs) for beam shaping in x-ray imaging. Two or more of these binary filters can be placed in an x-ray beam in series to permit a large number of x-ray fluence profiles. However, the relationship between particular MAD designs and the achievable fluence patterns is complex. The present invention includes mathematical and physical models that are used within an optimization framework to find optimal MAD designs. Specifically, given a set of target fluence patterns, the present invention finds, for example, a dual MAD design that is a “best fit” in generating the desired fluence patterns. This process provides a solution for both the design of MAD filters as well as the control actuation that is required (relative motion between MADs) that needs to be specified as part of the operation of a MAD-based fluence field modulation system.
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公开(公告)号：US20150262390A1
公开(公告)日：2015-09-17
申请号：US14404889
申请日：2013-05-31
IPC分类号： G06T11/00
CPC分类号： G06T11/006 , G06T2211/424
摘要： A framework, comprising techniques, process(es), device(s), system(s), combinations thereof, or the like, to analyze propagation of information in prior-image-based reconstruction by decomposing the estimation into distinct components supported by a current data acquisition and by a prior image. Such decomposition can quantify contributions from prior data and current data as a spatial map and/or can trace specific features in an image to a source of at least some of such features.
摘要翻译： 一种框架，包括技术，过程，设备，系统，其组合等，以通过将估计分解为由...所支持的不同组件来分析先前基于图像的重建中的信息的传播 当前数据采集和现有图像。 这种分解可以将来自先前数据和当前数据的贡献量化为空间图，和/或可以将图像中的特定特征跟踪到至少一些这样的特征的源。
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公开(公告)号：US20210174561A1
公开(公告)日：2021-06-10
申请号：US17110743
申请日：2020-12-03
摘要： Techniques for computed tomography (CT) image reconstruction are presented. The techniques can include acquiring, by a detector grid of a computed tomography system, detector signals for a location within an object of interest representing a voxel, where each detector signal of a plurality of the detector signals is obtained from an x-ray passing through the location at a different viewing angle; reconstructing a three-dimensional representation of at least the object of interest, the three-dimensional representation comprising the voxel, where the reconstructing comprises computationally perturbing a location of each detector signal of the plurality of detector signals within the detector grid, where the computationally perturbing corresponds to randomly perturbing a location of the x-ray within the voxel; and outputting the three-dimensional representation.
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公开(公告)号：US09936924B2
公开(公告)日：2018-04-10
申请号：US14780014
申请日：2014-03-26
CPC分类号： A61B6/032 , A61B6/12 , A61B6/4085 , A61B6/4441 , A61B6/485 , A61B6/5258 , A61B6/547 , G06T7/0012 , G06T7/30 , G06T11/005 , G06T15/08 , G06T2200/04 , G06T2207/10081 , G06T2207/10116 , G06T2207/30064 , G06T2207/30196 , G06T2211/421
摘要： An embodiment in accordance with the present invention provides a method for applying task-based performance predictors (measures of noise, spatial resolution, and detectability index) based on numerical observer models and approximations to the local noise and spatial resolution properties of the CBCT reconstruction process (e.g., penalized-likelihood iterative reconstruction). These predictions are then used to identify projections views (i.e., points that will constitute the scan trajectory) that maximize task performance, beginning with the projection view that maximizes detectability, proceeding to the next-best view, and continuing in an (arbitrarily constrained) orbit that can be physically realized on advanced robotic C-arm platforms. The performance of CBCT reconstructions arising from a task-based trajectory is superior to simple and complex orbits by virtue of improved spatial resolution and noise characteristics (relative to the specified imaging task) associated with the projection views constituting the customized scan orbit.
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5.发明申请公开(公告)号：US20180001111A1
公开(公告)日：2018-01-04
申请号：US15639044
申请日：2017-06-30
CPC分类号： A61N5/1077 , G01N23/00 , G01N2223/316 , G21K1/10
摘要： The present invention is directed to multiple aperture devices (MADs) for beam shaping in x-ray imaging. Two or more of these binary filters can be placed in an x-ray beam in series to permit a large number of x-ray fluence profiles. However, the relationship between particular MAD designs and the achievable fluence patterns is complex. The present invention includes mathematical and physical models that are used within an optimization framework to find optimal MAD designs. Specifically, given a set of target fluence patterns, the present invention finds, for example, a dual MAD design that is a “best fit” in generating the desired fluence patterns. This process provides a solution for both the design of MAD filters as well as the control actuation that is required (relative motion between MADs) that needs to be specified as part of the operation of a MAD-based fluence field modulation system.
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公开(公告)号：US20140363067A1
公开(公告)日：2014-12-11
申请号：US14370743
申请日：2013-01-10
CPC分类号： G06T11/008 , G06T7/38 , G06T11/005 , G06T2207/10081
摘要： A method for processing an image of a series of images includes receiving first data representing a first previously reconstructed image and receiving second data representing a second image. A second image is reconstructed in accordance with the first data, the second data and a noise model. The noise model is a likelihood estimation. The second image is reconstructed in accordance with a penalty function. The penalty function is a roughness penalty function. The penalty function is updated by iteratively adjusting an image volume estimate. The penalty function is updated by iteratively adjusting a registration term. The penalty function is a prior image penalty function and the prior image penalty function and a registration term are jointly optimized. The penalty function is determined in accordance with a noise model. The function is a p-norm penalty function.
摘要翻译： 一种用于处理一系列图像的图像的方法包括接收表示第一先前重建的图像的第一数据和接收表示第二图像的第二数据。 根据第一数据，第二数据和噪声模型重构第二图像。 噪声模型是似然估计。 根据惩罚函数重建第二个图像。 惩罚函数是粗糙度惩罚函数。 惩罚函数通过迭代地调整图像体积估计来更新。 惩罚函数通过迭代地调整注册项来更新。 惩罚函数是先验图像惩罚函数，并且联合优化了先前图像惩罚函数和注册项。 惩罚函数根据噪声模型确定。 该函数是一个p范数惩罚函数。
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公开(公告)号：US20170238897A1
公开(公告)日：2017-08-24
申请号：US15436042
申请日：2017-02-17
发明人： Jeffrey H. Siewerdsen , Yoshito Otake , Joseph Webster Stayman , Ali Uneri , Adam S. Wang , Sarah Ouadah
CPC分类号： A61B6/584 , A61B6/025 , A61B6/032 , A61B6/4085 , A61B6/4441 , A61B6/466 , A61B6/501 , A61B6/5205
摘要： The present invention is directed to a method for enabling volumetric image reconstruction from unknown projection geometry of tomographic imaging systems, including CT, cone-beam CT (CBCT), and tomosynthesis systems. The invention enables image reconstruction in cases where it was not previously possible (e.g., custom-designed trajectories on robotic C-arms, or systems using uncalibrated geometries), and more broadly offers improved image quality (e.g., improved spatial resolution and reduced streak artifact) and robustness to patient motion (e.g., inherent compensation for rigid motion) in a manner that does not alter the patient setup or imaging workflow. The method provides a means for accurately estimating the complete geometric description of each projection acquired during a scan by simulating various poses of the x-ray source and detector to determine their unique, scan-specific positions relative to the patient, which is often unknown or inexactly known (e.g., a custom-designed trajectory, or scan-to-scan variability in source and detector position).
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公开(公告)号：US20210307707A1
公开(公告)日：2021-10-07
申请号：US17288839
申请日：2019-10-25
摘要： The present invention is directed to spatial-spectral filtering for multi-material CT decomposition. The invention includes a specialized filter that spectrally shapes an x-ray beam into a number of beamlets with different spectra. The filter allows decomposition of an object/anatomy into different material categories (including different biological types: muscle, fat, etc. or exogenous contrast agents that have been introduced: e.g iodine, gadolinium, etc.). The x-ray beam is spectrally modulated across the face of the detector using a repeating pattern of filter materials. Such spatial-spectral filters allow for collection of many different spectral channels using “source-side” control. However, in contrast to other spectral techniques that provide mathematically complete projection data, spatial-spectral filtered data is sparse in each spectral channel—making traditional projection-domain or image-domain material decomposition difficult to apply. Therefore, the present invention uses model-based material decomposition, which combines reconstruction and multi-material decomposition, and permits arbitrary spectral, spatial, and angular sampling patterns.
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公开(公告)号：US10478148B2
公开(公告)日：2019-11-19
申请号：US15436042
申请日：2017-02-17
发明人： Jeffrey H. Siewerdsen , Yoshito Otake , Joseph Webster Stayman , Ali Uneri , Adam S. Wang , Sarah Ouadah
摘要： The present invention is directed to a method for enabling volumetric image reconstruction from unknown projection geometry of tomographic imaging systems, including CT, cone-beam CT (CBCT), and tomosynthesis systems. The invention enables image reconstruction in cases where it was not previously possible (e.g., custom-designed trajectories on robotic C-arms, or systems using uncalibrated geometries), and more broadly offers improved image quality (e.g., improved spatial resolution and reduced streak artifact) and robustness to patient motion (e.g., inherent compensation for rigid motion) in a manner that does not alter the patient setup or imaging workflow. The method provides a means for accurately estimating the complete geometric description of each projection acquired during a scan by simulating various poses of the x-ray source and detector to determine their unique, scan-specific positions relative to the patient, which is often unknown or inexactly known (e.g., a custom-designed trajectory, or scan-to-scan variability in source and detector position).
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公开(公告)号：US09626778B2
公开(公告)日：2017-04-18
申请号：US14404889
申请日：2013-05-31
CPC分类号： G06T11/006 , G06T2211/424
摘要： A framework, comprising techniques, process(es), device(s), system(s), combinations thereof, or the like, to analyze propagation of information in prior-image-based reconstruction by decomposing the estimation into distinct components supported by a current data acquisition and by a prior image. Such decomposition can quantify contributions from prior data and current data as a spatial map and/or can trace specific features in an image to a source of at least some of such features.
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