公开(公告)号：US09846935B2

公开(公告)日：2017-12-19

申请号：US14403292

申请日：2012-05-31

申请人： Sergey Simanovsky ,  Julia Pavlovich ,  Ram Naidu

发明人： Sergey Simanovsky ,  Julia Pavlovich ,  Ram Naidu

IPC分类号： G06K9/00 ,  G06T7/00 ,  G06T7/10 ,  G01V5/00 ,  G06K9/46 ,  G06K9/52 ,  G06T7/11

CPC分类号： G06T7/0012 ,  G01V5/0008 ,  G06K9/4609 ,  G06K9/52 ,  G06K2009/4666 ,  G06T7/10 ,  G06T7/11 ,  G06T2207/10081 ,  G06T2207/30112

摘要： Among other things, one or more systems and/or techniques for segmenting a representation of a sheet object from an image are provided herein. To identify elements of an image (e.g., pixels and/or voxels) representative of sheet objects, a constant false alarm rate (CFAR) score and a topological score are computed for respective elements being analyzed. The CFAR score indicates a relationship between an element and a neighborhood of elements when viewed as a collective unit. The topological score indicates a relationship between the element and a neighborhood of elements when viewed neighbor-by-neighbor. When the CFAR score is within a specified range of CFAR scores and the topological score is within a specified range of topological scores, the element is labeled as being associated with a sheet object. A connected component labeling (CCL) approach may be used to group elements labeled as being associated with a sheet object.

公开(公告)号：US20150104089A1

公开(公告)日：2015-04-16

申请号：US14397751

申请日：2012-05-01

申请人： Andrew Litvin ,  Ram Naidu ,  David Lieblich ,  Sergey Simanovsky

发明人： Andrew Litvin ,  Ram Naidu ,  David Lieblich ,  Sergey Simanovsky

IPC分类号： G06T11/00 ,  G01N23/04

CPC分类号： G06T11/006 ,  G01N23/046 ,  G06T2211/408 ,  G06T2211/424 ,  G06T2211/436

摘要： Z-effective (e.g., atomic number) values are generated for one or more sets of voxels in a CT density image using sparse (measured) multi-energy projection data. Voxels in the CT density image are assigned a starting z-effective value, causing a CT z-effective image to be generated from the CT density image. The accuracy of the assigned z-effective values is tested by forward projecting the CT z-effective image to generate synthetic multi-energy projection data and comparing the synthetic multi-energy projection data to the sparse multi-energy projection data. When the measure of similarity between the synthetic data and the sparse data is low, the z-effective value assigned to one or more voxels is modified until the measure of similarity is above a specified threshold (e.g., with an associated confidence score), at which point the z-effective values substantially reflect the z-effective values that would be obtained using a (more expensive) dual-energy CT imaging modality.

摘要翻译： 使用稀疏（测量）多能量投影数据，在CT密度图像中的一组或多组体素生成Z-有效（例如，原子序数）值。 CT密度图像中的体素被分配起始z有效值，从CT密度图像产生CT z有效图像。 通过向前投影CT z有效图像来产生合成多能量投影数据并将合成的多能量投影数据与稀疏多能量投影数据进行比较，来测试所分配的z-有效值的精度。 当合成数据和稀疏数据之间的相似性度量低时，分配给一个或多个体素的z-有效值被修改，直到相似性的度量高于指定的阈值（例如，具有相关的可信度得分），在 这指出z-有效值基本上反映了使用（更昂贵）双能CT成像模式将获得的z-有效值。

公开(公告)号：US08787669B2

公开(公告)日：2014-07-22

申请号：US13121892

申请日：2008-09-30

申请人： Andrew Litvin ,  Sergey Simanovsky ,  Ram Naidu

发明人： Andrew Litvin ,  Sergey Simanovsky ,  Ram Naidu

IPC分类号： G06K9/34

CPC分类号： G06T7/155

摘要： Representations of an object can comprise two or more separate sub-objects, producing a compound object. Compound objects can affect the quality of object visualization and threat identification. As provided herein, a compound object can be separated into sub-objects based on object morphological properties (e.g., an object's shape, surface area). Further, a potential compound object can be split into sub-objects, for example, eroding one or more outer layers of volume space (e.g., voxels) from the potential compound object. Additionally, a volume of a representation of the sub-objects in an image can be reconstructed, for example, by generating sub-objects that have a combined volume approximate to that of the compound object. Furthermore, sub-objects, which can be parts of a same physical object, but may have been erroneously split, can be identified and merged using connectivity and compactness based techniques.

摘要翻译： 对象的表示可以包括两个或多个单独的子对象，产生复合对象。 复合对象可以影响对象可视化和威胁识别的质量。 如本文所提供的，可以基于对象形态特性（例如，对象的形状，表面积）将复合对象分成子对象。 此外，潜在的复合对象可以被分割成子对象，例如，从潜在的复合对象侵蚀体积空间的一个或多个外层（例如，体素）。 此外，可以例如通过生成具有近似于复合对象的组合体积的子对象来重建图像中子对象的表示量。 此外，可以使用基于连接性和紧凑性的技术来识别和合并可以是相同物理对象的部分但可能被错误地分割的子对象。

公开(公告)号：US07539337B2

公开(公告)日：2009-05-26

申请号：US11183378

申请日：2005-07-18

申请人： Sergey Simanovsky ,  Zhengrong Ying ,  Carl R. Crawford

发明人： Sergey Simanovsky ,  Zhengrong Ying ,  Carl R. Crawford

IPC分类号： G06K9/00

CPC分类号： G06K9/00771 ,  G01T1/2985 ,  G01V5/0041 ,  G01V5/005 ,  G06K9/6219

摘要： A method of and a system for splitting a compound object using multi-energy CT data including a density and an atomic number measurements are provided. The method comprises: compound object detection; computing a two-dimensional DZ distribution of a compound object; identifying clusters within the DZ distribution; assigning a component label to each object voxel based on the DZ distribution clusters; and post-processing the set of voxels identified as belonging to each component.

摘要翻译： 提供了使用包括密度和原子序数测量的多能量CT数据来分割复合对象的方法和系统。 该方法包括：复合物体检测; 计算复合对象的二维DZ分布; 识别DZ分布中的簇; 基于DZ分布集群为每个对象体素分配一个组件标签; 并且后处理被识别为属于每个组件的一组体素。

公开(公告)号：US07302083B2

公开(公告)日：2007-11-27

申请号：US10883199

申请日：2004-07-01

申请人： Gregory L. Larson ,  Sergey Simanovsky ,  Zhengrong Ying ,  Carl R. Crawford

发明人： Gregory L. Larson ,  Sergey Simanovsky ,  Zhengrong Ying ,  Carl R. Crawford

IPC分类号： G06K9/00 ,  G01N23/04

CPC分类号： G06T7/0004 ,  G06T2207/10081 ,  G06T2207/30112

摘要： A method of and a system for sharp object detection using computed tomography images are provided. The method comprises identifying voxels corresponding to individual objects; performing eigen-analysis and generating eigen-projection of an identified object; computing an axial concavity ratio of the identified object; computing a pointness measurement of the identified object; computing a flat area of the identified object; calculating a sharpness score of the identified object; and declaring the identified object as a threat if the sharpness score is greater than a pre-defined threshold.

摘要翻译： 提供了使用计算机断层摄影图像进行尖锐物体检测的方法和系统。 该方法包括识别与各个对象相对应的体素; 执行特征分析并产生识别对象的特征投影; 计算所识别的物体的轴向凹度比; 计算所识别对象的点测量; 计算所识别对象的平坦区域; 计算识别对象的锐度得分; 并且如果清晰度得分大于预定义的阈值，则将所识别的对象声明为威胁。

公开(公告)号：US07190757B2

公开(公告)日：2007-03-13

申请号：US10850910

申请日：2004-05-21

申请人： Zhengrong Ying ,  Ram Naidu ,  Sergey Simanovsky ,  Carl R. Crawford

发明人： Zhengrong Ying ,  Ram Naidu ,  Sergey Simanovsky ,  Carl R. Crawford

IPC分类号： A61B6/00

CPC分类号： G01N23/046 ,  G01N2223/419

摘要： A method of and a system for computing Z (effective atomic number) images from projection data are provided, wherein the projections are acquired using at least two x-ray spectra for a set of scanned objects, including a set of low energy projections and a set of high energy projections; the method comprises decomposing the low energy projections and high energy projections into photoelectric projections, reconstructing the photoelectric projections into photoelectric images, reconstructing one of the two sets of projections into CT images, and computing Z images from the CT images and the photoelectric images with parameters obtained from a calibration procedure.

摘要翻译： 提供了一种用于从投影数据计算Z（有效原子序号）图像的方法和系统，其中使用用于一组扫描对象的至少两个X射线光谱来获取投影，包括一组低能量投影和 一套高能量投影; 该方法包括将低能量投影和高能量投影分解为光电投影，将光电投影重建为光电图像，将两组投影中的一个重建为CT图像，并从CT图像和光电图像中计算Z图像 从校准程序获得。

公开(公告)号：US20060274066A1

公开(公告)日：2006-12-07

申请号：US11142216

申请日：2005-06-01

申请人： Zhengrong Ying ,  Matthew Hirsch ,  Purvin Desai ,  Kyle Guilbert ,  Sergey Simanovsky ,  Carl Crawford

发明人： Zhengrong Ying ,  Matthew Hirsch ,  Purvin Desai ,  Kyle Guilbert ,  Sergey Simanovsky ,  Carl Crawford

IPC分类号： G06T17/00

CPC分类号： A61B6/482 ,  A61B6/03 ,  G01V5/0041 ,  G01V5/005 ,  G06T11/008

摘要： A method of and a system for displaying volumetric multi-energy CT images are disclosed, wherein a CT image, a Z image, and a label image from an automatic explosive detection are provided, are disclosed. The method comprises generating an index image through a nonlinear transformation of the CT image, the Z image, and the label image, rotating and coloring the index image as desired, and rendering and displaying the rotated and colored image.

摘要翻译： 公开了一种用于显示体积多能CT图像的方法和系统，其中提供了CT图像，Z图像和来自自动爆炸检测的标签图像。 该方法包括通过CT图像，Z图像和标签图像的非线性变换生成索引图像，根据需要旋转和着色索引图像，以及渲染和显示旋转和着色图像。

公开(公告)号：US20060002585A1

公开(公告)日：2006-01-05

申请号：US10883199

申请日：2004-07-01

申请人： Gregory Larson ,  Sergey Simanovsky ,  Zhengrong Ying ,  Carl Crawford

发明人： Gregory Larson ,  Sergey Simanovsky ,  Zhengrong Ying ,  Carl Crawford

IPC分类号： G06K9/00

CPC分类号： G06T7/0004 ,  G06T2207/10081 ,  G06T2207/30112

摘要： A method of and a system for sharp object detection using computed tomography images are provided. The method comprises identifying voxels corresponding to individual objects; performing eigen-analysis and generating eigen-projection of an identified object; computing an axial concavity ratio of the identified object; computing a pointness measurement of the identified object; computing a flat area of the identified object; calculating a sharpness score of the identified object; and declaring the identified object as a threat if the sharpness score is greater than a pre-defined threshold.

摘要翻译： 提供了使用计算机断层摄影图像进行尖锐物体检测的方法和系统。 该方法包括识别与各个对象相对应的体素; 执行特征分析并产生识别对象的特征投影; 计算所识别的物体的轴向凹度比; 计算所识别对象的点测量; 计算所识别对象的平坦区域; 计算识别对象的锐度得分; 并且如果清晰度得分大于预定义的阈值，则将所识别的对象声明为威胁。

公开(公告)号：US06317509B1

公开(公告)日：2001-11-13

申请号：US09022059

申请日：1998-02-11

申请人： Sergey Simanovsky ,  Ibrahim M. Bechwati ,  Muzaffer Hiraoglu ,  Carl R. Crawford

发明人： Sergey Simanovsky ,  Ibrahim M. Bechwati ,  Muzaffer Hiraoglu ,  Carl R. Crawford

IPC分类号： G06K900

CPC分类号： G01V5/005 ,  G01N33/22 ,  G06K9/00771 ,  G06K2209/09

摘要： A method and apparatus detects sheet explosives in computed tomography (CT) data. In particular, sheet-shaped objects such as sheet explosives can be discriminated from other object shapes and detected. The detection includes analyzing a neighborhood of voxels surrounding a test voxel. If the density of the test voxel is sufficiently different from the mean density of the neighboring voxels, then it is concluded that the test voxel is associated with a sheet object. Sheet objects can also be detected by eroding the CT data so as to eliminate voxels associated with thin objects. Remaining objects are then subtracted from the original data, leaving only thin sheet-shaped objects. Erosion of the data can be performed by identifying a neighborhood of voxels surrounding a voxel of interest. If the number of voxels having densities below a predetermined threshold exceeds a predetermined number, then it is assumed that the test voxel is a surface voxel and is removed from the object. A connectivity process can be applied to voxels to combine them into objects after sheets are detected to prevent sheets from being inadvertently removed from the data by erosion. A dilation function can then be performed on the eroded object to replace surface voxels removed by erosion. A corrected mass using the mean eroded density of the object can be computed and compared to mass thresholds to classify the object as to whether it poses a threat. Multiple mass thresholds can be used, each of which is associated with a particular density range based on the density of an expected threat object.

摘要翻译： 计算机断层摄影（CT）数据中的方法和装置检测片状炸药。 特别地，片状物体如片状炸药可以与其他物体形状区分开来并进行检测。 检测包括分析围绕测试体素的体素的邻域。 如果测试体素的密度与相邻体元的平均密度有很大的不同，则可以得出结论，测试体素与片材物体相关联。 也可以通过侵蚀CT数据来检测片材物体，以消除与薄物体相关联的体素。 然后从原始数据中减去剩余对象，只留下薄片状物体。 可以通过识别感兴趣的体素周围的体素的邻域来执行数据的侵蚀。 如果具有低于预定阈值的密度的体素的数量超过预定数量，则假设测试体素是表面体素并且从对象中移除。 可以将连接过程应用于体素，以便在检测到页面之后将其组合到对象中，以防止纸张被侵蚀从而无意中从数据中移除。 然后可以对侵蚀的物体执行扩张功能，以取代被侵蚀除去的表面体素。 可以计算使用对象的平均侵蚀密度的校正质量，并将其与质量阈值进行比较，以对对象是否构成威胁进行分类。 可以使用多个质量阈值，每个质量阈值基于预期威胁对象的密度与特定密度范围相关联。

公开(公告)号：US20150139491A1

公开(公告)日：2015-05-21

申请号：US14408283

申请日：2012-06-29

申请人： Sergey Simanovsky ,  Ram Naidu

发明人： Sergey Simanovsky ,  Ram Naidu

IPC分类号： G06T7/00 ,  G01V5/00 ,  G01N23/04

CPC分类号： G06T7/0006 ,  G01N23/046 ,  G01V5/005 ,  G06T7/0004 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/136 ,  G06T2207/10081 ,  G06T2207/30112

摘要： Among other things, one or more systems and/or techniques for identifying an occlusion region in an image representative of an object subjected to examination is provided for herein. Such systems and/or techniques may find particular application in the context of object recognition analysis. An image is generated of the object and an orientation of the object is determined from the image. Based upon the determined orientation of the object relative to the direction the object is translated during examination, one or more parameters utilized for segmenting a second image of the object, identifying features in the image, and/or determining if the image comprises an occlusion region may be adjusted. In this way, the parameters utilized may be a function of the determined orientation of the object, which may mitigate false positives of detected occlusion regions.

摘要翻译： 除此之外，还提供了一种或多种用于识别代表检查对象的图像中的遮挡区域的系统和/或技术。 这样的系统和/或技术可以在对象识别分析的上下文中找到特定的应用。 生成对象的图像，并根据图像确定对象的方位。 基于物体在检查期间相对于物体被转换的方向的确定的取向，用于分割对象的第二图像的一个或多个参数，识别图像中的特征，和/或确定图像是否包括遮挡区域 可以调整。 以这种方式，所使用的参数可以是所确定的物体取向的函数，其可以减轻检测到的遮挡区域的误报。