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    • 3. 发明申请
    • Viewing Three Dimensional Digital Slides
    • 查看三维数字幻灯片
    • US20120235994A1
    • 2012-09-20
    • US13482869
    • 2012-05-29
    • Ole Eichhorn
    • Ole Eichhorn
    • G06T15/00
    • G06T15/00G02B21/34G02B21/367G06T5/50G06T15/08G06T15/10G06T2207/20212G06T2207/20224G06T2207/30024G06T2207/30056
    • Systems and methods for retrieving, manipulating, and viewing 3D image objects from 3D virtual microscope slide images (“3D digital slides”) are provided. An image library module provides access to the imagery data in a 3D digital slide and constructs 3D image objects that are coextensive with the 3D digital slide or a 3D sub-portion thereof. From within the 3D image object, cross layer planar views spanning various depths of the 3D digital slide are constructed as well as 3D prisms and other shaped image areas. The image library module allows a 3D image object to be sliced into horizontal and vertical views, skewed cross layer views and regular and irregular shaped 3D image areas for viewing by a user.
    • 提供了从3D虚拟显微镜幻灯片图像(“3D数字幻灯片”)中检索,操纵和查看3D图像对象的系统和方法。 图像库模块提供对3D数字幻灯片中的图像数据的访问,并且构建与3D数字幻灯片或其3D子部分共同延伸的3D图像对象。 从3D图像对象中,构建跨越3D数字幻灯片的各种深度的跨层平面视图以及3D棱镜和其他形状图像区域。 图像库模块允许3D图像对象被切割成水平和垂直视图,倾斜的交叉层视图和规则和不规则形状的3D图像区域以供用户观看。
    • 5. 发明申请
    • Signal to Noise Ratio in Digital Pathology Image Analysis
    • 数字病理图像分析中的信噪比
    • US20120014576A1
    • 2012-01-19
    • US13259562
    • 2010-12-10
    • Allen OlsonOle Eichhorn
    • Allen OlsonOle Eichhorn
    • G06K9/00
    • G06T7/0012G06F19/00G06F19/321G06T2207/10056G06T2207/30024
    • A digital slide analysis system comprises an algorithm server that maintains or has access to a plurality of image processing and analysis routines. The algorithm server additionally has access to a plurality of digital slide images. The algorithm server executes a selected routine on an identified digital slide and provides the resulting data. Prior to the application of selected routine, the system employs a digital pre-processing module to create a metadata mask that reduces undesirable image data such that the image data processed by the selected routine has an improved signal to noise ratio. The pre-processing module uses a classifier that may be implemented as a pattern recognition module, for example. Undesirable image data is therefore excluded from the image data that is processed by the digital pathology image processing and analysis routine, which significantly improves the digital pathology image analysis.
    • 数字幻灯片分析系统包括维护或者可以访问多个图像处理和分析程序的算法服务器。 算法服务器还可以访问多个数字幻灯片图像。 算法服务器在识别的数字幻灯片上执行所选择的例程,并提供所得到的数据。 在应用所选程序之前,系统采用数字预处理模块来创建一个减少不需要的图像数据的元数据掩码,使得由所选程序处理的图像数据具有改善的信噪比。 预处理模块使用例如可以被实现为模式识别模块的分类器。 因此,不希望的图像数据被排除在由数字病理图像处理和分析程序处理的图像数据中,这显着地改善了数字病理图像分析。
    • 7. 发明授权
    • Systems and methods for image pattern recognition
    • 图像模式识别的系统和方法
    • US07844125B2
    • 2010-11-30
    • US12400981
    • 2009-03-10
    • Ole EichhornDirk G. Soenksen
    • Ole EichhornDirk G. Soenksen
    • G06K9/00G06K9/68
    • G06K9/6218G06K9/00147G06T9/008G06T9/40H04N19/94H04N19/96
    • Systems and methods for image pattern recognition comprise digital image capture and encoding using vector quantization (“VQ”) of the image. A vocabulary of vectors is built by segmenting images into kernels and creating vectors corresponding to each kernel. Images are encoded by creating a vector index file having indices that point to the vectors stored in the vocabulary. The vector index file can be used to reconstruct an image by looking up vectors stored in the vocabulary. Pattern recognition of candidate regions of images can be accomplished by correlating image vectors to a pre-trained vocabulary of vector sets comprising vectors that correlate with particular image characteristics. In virtual microscopy, the systems and methods are suitable for rare-event finding, such as detection of micrometastasis clusters, tissue identification, such as locating regions of analysis for immunohistochemical assays, and rapid screening of tissue samples, such as histology sections arranged as tissue microarrays (“TMAs”).
    • 用于图像模式识别的系统和方法包括使用图像的矢量量化(“VQ”)的数字图像捕获和编码。 通过将图像分割为内核并创建与每个内核相对应的向量来构建向量的词汇表。 通过创建具有指向存储在词汇表中的向量的索引的向量索引文件对图像进行编码。 向量索引文件可用于通过查找存储在词汇表中的向量来重建图像。 可以通过将图像向量与包括与特定图像特征相关的向量的预先训练的矢量集合的词汇相关联来实现图像的候选区域的模式识别。 在虚拟显微镜中,系统和方法适用于罕见事件发现,例如检测微转移簇,组织鉴定,例如免疫组织化学测定的分析区域以及组织样品的快速筛选,例如排列成组织的组织切片 微阵列(“TMA”)。
    • 10. 发明申请
    • Systems and Methods for Image Pattern Recognition
    • 图像模式识别系统与方法
    • US20070274603A1
    • 2007-11-29
    • US11836713
    • 2007-08-09
    • Ole EichhornDirk Soenksen
    • Ole EichhornDirk Soenksen
    • G06K9/36
    • G06K9/6218G06K9/00147G06T9/008G06T9/40H04N19/94H04N19/96
    • Systems and methods for image pattern recognition comprise digital image capture and encoding using vector quantization (“VQ”) of the image. A vocabulary of vectors is built by segmenting images into kernels and creating vectors corresponding to each kernel. Images are encoded by creating a vector index file having indices that point to the vectors stored in the vocabulary. The vector index file can be used to reconstruct an image by looking up vectors stored in the vocabulary. Pattern recognition of candidate regions of images can be accomplished by correlating image vectors to a pre-trained vocabulary of vector sets comprising vectors that correlate with particular image characteristics. In virtual microscopy, the systems and methods are suitable for rare-event finding, such as detection of micrometastasis clusters, tissue identification, such as locating regions of analysis for immunohistochemical assays, and rapid screening of tissue samples, such as histology sections arranged as tissue microarrays (TMAs).
    • 用于图像模式识别的系统和方法包括使用图像的矢量量化(“VQ”)的数字图像捕获和编码。 通过将图像分割为内核并创建与每个内核相对应的向量来构建向量的词汇表。 通过创建具有指向存储在词汇表中的向量的索引的向量索引文件对图像进行编码。 向量索引文件可用于通过查找存储在词汇表中的向量来重建图像。 可以通过将图像向量与包括与特定图像特征相关的向量的预先训练的矢量集合词汇相关联来实现图像候选区域的模式识别。 在虚拟显微镜中,系统和方法适用于罕见事件发现,例如检测微转移簇,组织鉴定,例如免疫组织化学测定的分析区域以及组织样品的快速筛选,例如排列成组织的组织切片 微阵列(TMA)。