METHOD FOR OPTIMIZING RADIATION BEAM INTENSITY PROFILE SHAPE USING DUAL MULTIPLE APERTURE DEVICES

    公开(公告)号:US20220088417A1

    公开(公告)日:2022-03-24

    申请号:US17545030

    申请日:2021-12-08

    IPC分类号: A61N5/10 G01N23/00 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.

    INFORMATION PROPAGATION IN PRIOR-IMAGE-BASED RECONSTRUCTION
    2.
    发明申请
    INFORMATION PROPAGATION IN PRIOR-IMAGE-BASED RECONSTRUCTION 有权
    基于先前图像重建的信息传播

    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。

    STOCHASTIC BACKPROJECTION FOR 3D IMAGE RECONSTRUCTION

    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.

    METHOD FOR OPTIMIZING RADIATION BEAM INTENSITY PROFILE SHAPE USING DUAL MULTIPLE APERTURE DEVICES

    公开(公告)号:US20180001111A1

    公开(公告)日:2018-01-04

    申请号:US15639044

    申请日:2017-06-30

    IPC分类号: A61N5/10 G01N23/00

    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.

    METHODS AND SYSTEMS FOR TOMOGRAPHIC RECONSTRUCTION
    6.
    发明申请
    METHODS AND SYSTEMS FOR TOMOGRAPHIC RECONSTRUCTION 有权
    TOMOGRAPHIC重建的方法和系统

    公开(公告)号:US20140363067A1

    公开(公告)日:2014-12-11

    申请号:US14370743

    申请日:2013-01-10

    IPC分类号: G06T11/00 G06T7/00

    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。

    SELF-CALIBRATING PROJECTION GEOMETRY FOR VOLUMETRIC IMAGE RECONSTRUCTION

    公开(公告)号:US20170238897A1

    公开(公告)日:2017-08-24

    申请号:US15436042

    申请日:2017-02-17

    IPC分类号: A61B6/00 A61B6/03

    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).

    Spatial-Spectral Filters for Multi-Material Decomposition in Computed Tomography

    公开(公告)号:US20210307707A1

    公开(公告)日:2021-10-07

    申请号:US17288839

    申请日:2019-10-25

    IPC分类号: A61B6/00 A61B6/03

    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.

    Self-calibrating projection geometry for volumetric image reconstruction

    公开(公告)号:US10478148B2

    公开(公告)日:2019-11-19

    申请号:US15436042

    申请日:2017-02-17

    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).