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    • 3. 发明授权
    • Iterative reconstruction methods for multi-slice computed tomography
    • 多层计算机断层扫描的迭代重建方法
    • US06907102B1
    • 2005-06-14
    • US10319674
    • 2002-12-16
    • Ken SauerCharles A. BoumanJean-Baptiste ThibaultJiang Hsieh
    • Ken SauerCharles A. BoumanJean-Baptiste ThibaultJiang Hsieh
    • A61B6/03G06T11/00A61B6/00
    • G06T11/006A61B6/027A61B6/032A61B6/4085G06T2211/424Y10S378/901
    • A multi-slice computed tomography imaging system is provided including a source that generates an x-ray beam and a detector array that receives the x-ray beam and generates projection data. A translatable table has an object thereon and is operable to translate in relation to the source and the detector array. The source and the detector array rotate about the translatable table to helically scan the object. An image reconstructor is electrically coupled to the detector array and reconstructs an image in response to the projection data using a computed tomography modeled iterative reconstruction technique. The iterative reconstruction technique includes determining a cross-section reconstruction vector, which approximately matches the projection data via a computed tomography model. Methods for performing the same are also provided including accounting for extended boundary regions.
    • 提供了一种多切片计算机断层摄影成像系统,其包括产生X射线束的源和接收X射线束并产生投影数据的检测器阵列。 一个可翻译的桌子上有一个物体,它可以相对于源和检测器阵列进行平移。 源和检测器阵列绕可翻译表旋转以螺旋扫描对象。 图像重构器电耦合到检测器阵列,并且使用计算机断层摄影建模的迭代重建技术来响应于投影数据重建图像。 迭代重建技术包括确定通过计算机断层摄影模型近似匹配投影数据的横截面重建矢量。 还提供了用于执行该方法的方法,包括扩展边界区域的计算。
    • 7. 发明申请
    • METHODS AND SYSTEM FOR ANALYZING AND RATING IMAGES FOR PERSONALIZATION
    • 用于分析和评估个性化图像的方法和系统
    • US20130182946A1
    • 2013-07-18
    • US13349751
    • 2012-01-13
    • Raja BalaZhigang FanHengzhou DingJan P. AllebachCharles A. BoumanReuven J. Sherwin
    • Raja BalaZhigang FanHengzhou DingJan P. AllebachCharles A. BoumanReuven J. Sherwin
    • G06K9/46G06K9/62
    • G06K9/00671G06K9/3258
    • As set forth herein, a computer-implemented method facilitates pre-analyzing an image and automatically suggesting to the user the most suitable regions within an image for text-based personalization. Image regions that are spatially smooth and regions with existing text (e.g. signage, banners, etc.) are primary candidates for personalization. This gives rise to two sets of corresponding algorithms: one for identifying smooth areas, and one for locating text regions. Smooth regions are found by dividing the image into blocks and applying an iterative combining strategy, and those regions satisfying certain spatial properties (e.g. size, position, shape of the boundary) are retained as promising candidates. In one embodiment, connected component analysis is performed on the image for locating text regions. Finally, based on the smooth and text regions found in the image, several alternative approaches are described herein to derive an overall metric for “suitability for personalization.”
    • 如本文所述,计算机实现的方法有助于预分析图像并且自动地向用户建议图像内的最合适的区域用于基于文本的个性化。 具有空间平滑的图像区域和具有现有文本的区域(例如标牌,横幅等)是用于个性化的主要候选者。 这产生了两组相应的算法:一种用于识别平滑区域,一种用于定位文本区域。 通过将图像划分成块并应用迭代组合策略来找到平滑区域,并且满足某些空间属性(例如,边界的大小,位置,形状)的那些区域被保留为有希望的候选者。 在一个实施例中,对用于定位文本区域的图像执行连接分量分析。 最后,基于图像中发现的平滑和文本区域,本文描述了几种替代方法,以得出“适合个性化”的总体度量。