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    • 1. 发明授权
    • Method and apparatus for analyzing body fluids
    • 用于分析体液的方法和装置
    • US08391608B2
    • 2013-03-05
    • US12902947
    • 2010-10-12
    • Richard H. TurnerEric Chapoulaud
    • Richard H. TurnerEric Chapoulaud
    • G06K9/46G06K9/00E03B1/00C12Q1/00G01N33/48G01N21/64
    • G01N15/1459G01N15/1463G01N2015/0069G01N2015/0073G01N2015/008G01N2015/1486Y10T137/0352
    • A system and method for analyzing a specimen containing particles that can be difficult to differentiate. The system and method determines a first collective count of a selected group of particles in the specimen, treats at least a portion of the specimen to alter a subgroup of the selected group of particles, determines a second collective count of any of the selected group of particles in the treated portion of the specimen, and subtracts the second collective count from the first collective count to determine a differentiation count for the subgroup of particles altered by the treating of the specimen. The system and method is described with the example of determining concentrations of red and white blood cells in a specimen (e.g. spinal fluid), using auto-particle recognition techniques, without attempting to distinguish and count red versus white blood cells co-existing in the same specimen portion.
    • 用于分析含有可能难以区分的颗粒的样品的系统和方法。 系统和方法确定样本中所选择的一组颗粒的第一集合计数,处理样本的至少一部分以改变所选择的一组颗粒的亚组,确定所选择的组中的任何组的第二集合计数 在样品的处理部分中的颗粒,并从第一集合计数中减去第二集合计数,以确定通过处理样品而改变的颗粒亚组的分化计数。 以使用自动粒子识别技术确定样品(例如脊髓液)中的红细胞和白细胞的浓度的实例来描述系统和方法,而不试图区分和计数共存于 相同的标本部分。
    • 2. 发明授权
    • Method and apparatus for analyzing body fluids
    • 用于分析体液的方法和装置
    • US07822276B2
    • 2010-10-26
    • US11354603
    • 2006-02-14
    • Richard H. TurnerEric Chapoulaud
    • Richard H. TurnerEric Chapoulaud
    • G06K9/46G06K9/00E03B1/00C12Q1/00
    • G01N15/1459G01N15/1463G01N2015/0069G01N2015/0073G01N2015/008G01N2015/1486Y10T137/0352
    • A system and method for analyzing a specimen containing particles that can be difficult to differentiate. The system and method determines a first collective count of a selected group of particles in the specimen, treats at least a portion of the specimen to alter a subgroup of the selected group of particles, determines a second collective count of any of the selected group of particles in the treated portion of the specimen, and subtracts the second collective count from the first collective count to determine a differentiation count for the subgroup of particles altered by the treating of the specimen. The system and method is described with the example of determining concentrations of red and white blood cells in a specimen (e.g. spinal fluid), using auto-particle recognition techniques, without attempting to distinguish and count red versus white blood cells co-existing in the same specimen portion.
    • 用于分析含有可能难以区分的颗粒的样品的系统和方法。 系统和方法确定样本中所选择的一组颗粒的第一集合计数,处理样本的至少一部分以改变所选择的一组颗粒的亚组,确定所选择的组中的任何组的第二集合计数 在样品的处理部分中的颗粒,并从第一集合计数中减去第二集合计数,以确定通过处理样品而改变的颗粒亚组的分化计数。 以使用自动粒子识别技术确定样品(例如脊髓液)中的红细胞和白细胞的浓度的实例来描述系统和方法,而不试图区分和计数共存于 相同的标本部分。
    • 3. 发明申请
    • Method And Apparatus For Analyzing Body Fluids
    • 用于分析体液的方法和装置
    • US20110027824A1
    • 2011-02-03
    • US12902947
    • 2010-10-12
    • Richard H. TurnerEric Chapoulaud
    • Richard H. TurnerEric Chapoulaud
    • C12Q1/06G06K9/00
    • G01N15/1459G01N15/1463G01N2015/0069G01N2015/0073G01N2015/008G01N2015/1486Y10T137/0352
    • A system and method for analyzing a specimen containing particles that can be difficult to differentiate. The system and method determines a first collective count of a selected group of particles in the specimen, treats at least a portion of the specimen to alter a subgroup of the selected group of particles, determines a second collective count of any of the selected group of particles in the treated portion of the specimen, and subtracts the second collective count from the first collective count to determine a differentiation count for the subgroup of particles altered by the treating of the specimen. The system and method is described with the example of determining concentrations of red and white blood cells in a specimen (e.g. spinal fluid), using auto-particle recognition techniques, without attempting to distinguish and count red versus white blood cells co-existing in the same specimen portion.
    • 用于分析含有可能难以区分的颗粒的样品的系统和方法。 系统和方法确定样本中所选择的一组颗粒的第一集合计数,处理样本的至少一部分以改变所选择的一组颗粒的亚组,确定所选择的组中的任何组的第二集合计数 在样品的处理部分中的颗粒,并从第一集合计数中减去第二集合计数,以确定通过处理样品而改变的颗粒亚组的分化计数。 以使用自动粒子识别技术确定样品(例如脊髓液)中的红细胞和白细胞的浓度的实例来描述系统和方法,而不试图区分和计数共存于 相同的标本部分。
    • 8. 发明授权
    • Particle extraction for automatic flow microscope
    • 自动流动显微镜的粒子提取
    • US07702172B2
    • 2010-04-20
    • US10716253
    • 2003-11-17
    • Eric Chapoulaud
    • Eric Chapoulaud
    • G06K9/42
    • G01N15/1475G01N15/147G06T7/12G06T7/194G06T2207/30024
    • A method and apparatus for locating the boundary of an object. An electronic image of the object is formed, having a plurality of image pixels. Groups of the image pixels are identified that represent edge segments of the object. Patches are formed around the image pixel groups, where each patch is dimensioned and positioned to entirely contain one of the image pixel groups. A patch merge process is preformed that merges any two of the patches together that overlap each other by a predetermined amount, to form a merged patch that is dimensioned and positioned to entirely contain the two merged patches. The merge process continues for any overlapping patches and merged patches until none of the patches and the merged patches overlap each other by the predetermined amount. All the edge segments contained within one of the merged patches are associated as representing the boundary of the object.
    • 一种用于定位物体边界的方法和装置。 形成具有多个图像像素的物体的电子图像。 识别表示对象的边缘段的图像像素组。 贴片形成在图像像素组周围,其中每个贴片的尺寸和位置被完全包含一个图像像素组。 执行补丁合并过程,将任何两个补丁合并在一起,彼此重叠预定量,以形成被整合并定位成完全包含两个合并补丁的合并补丁。 对于任何重叠的修补程序和合并的补丁,合并进程将继续进行,直到补丁和合并的修补程序中的任何一个重叠彼此重叠为预定的量。 包含在一个合并的补丁中的所有边缘段都与表示对象的边界相关联。
    • 9. 发明申请
    • Fluid sample analysis using class weights
    • 使用等级权重的流体样本分析
    • US20050008228A1
    • 2005-01-13
    • US10850786
    • 2004-05-21
    • Eric ChapoulaudHarvey Kasdan
    • Eric ChapoulaudHarvey Kasdan
    • G01N20060101G01N15/14G06K9/03G06K9/62
    • G06K9/00127G01N15/1429G01N15/1463G01N2015/1465G01N2015/1486G01N2015/1488
    • Most automatic particle classification methods produce errors. The invention provides a method for improving the accuracy of particle classification while shortening the amount of manual review time required from the operator. The method uses class weights, which are statistically-derived correction factors that accounts for frequency of classification errors. A first class weight and a second class weight are assigned to the first class and the second class, respectively. The number of particles in each of the first and the second classes is multiplied by the first class weight and the second class weight, respectively, to generate a corrected number of particles in each of the classes. If particles are reclassified, the class weights are recalculated in response to the reclassification. The method is usable with a complete classification where all the particles in a sample are classified, or a selective classification of a subset of the particles in the sample.
    • 大多数自动粒子分类方法产生错误。 本发明提供了一种提高粒子分级精度的方法,同时缩短了操作者所需的手动审查时间。 该方法使用类权重,这是统计学派生的校正因子,考虑到分类错误的频率。 第一类和第二类的权重分别分配给第一类和第二类。 第一类和第二类中的每一个中的粒子数分别乘以第一等级权重和第二类权重,以在每个类中生成校正的粒子数。 如果粒子重新分类,则根据重新分类重新计算类别权重。 该方法可用于将样品中所有颗粒分类的完整分类,或样品中颗粒子集的选择性分类。
    • 10. 发明授权
    • Custom orthodontic appliance forming method and apparatus
    • 定制矫正器具的形成方法和装置
    • US08690568B2
    • 2014-04-08
    • US09941151
    • 2001-08-28
    • Eric ChapoulaudCraig A. AndreikoMark A. Payne
    • Eric ChapoulaudCraig A. AndreikoMark A. Payne
    • A61C3/00
    • A61C7/00A61C7/002A61C7/146A61C13/0004A61C13/0019A61C2007/004B33Y80/00
    • A system (10) and method by which an orthodontic appliance (25) is automatically designed and manufactured from digital lower jaw and tooth shape data of a patient provides for the scanning of the mouth of a patient (12), preferably from a model (20) of the patient's mouth, to produce a three-dimensional digitized model (26) of the shapes of the patient's teeth and their positions in the patient's mouth. Then a computer (30) calculates the post-treatment positions of the teeth and produces three-dimensional images of the teeth, individually and in their calculated positions. An interactive computer link between the doctor's office (11) and the appliance manufacturing facility (13) allows an orthodontist (14) to control the patient's archform and to modify the suggested computer-determined positions and orientations of the teeth in six degrees of freedom, and to experiment with new positions, extractions, over-corrections and other variations, with the computer recalculating the tooth positions with high precision for the approval of the orthodontist. The appliance is automatically designed according to the final design, which also can be interactively modified and approved by the orthodontist, with the computer recalculating the effects on the treatment as a result of the doctor's changes. Brackets (81) are fabricated as an integrated set, either by cutting slots therein or by building the brackets in layers by, for example, stereo lithography. Three-dimensional custom jigs (87) are automatically made to exactly position the brackets on a patient's teeth.
    • 由患者的数字下颌和牙齿形状数据自动设计和制造矫正器具(25)的系统(10)和方法提供了对患者(12)的口部的扫描,优选地从模型 20),以产生患者牙齿形状及其在患者口腔中的位置的三维数字化模型(26)。 然后,计算机(30)计算牙齿的后处理位置,并且分别产生牙齿的三维图像并且以其计算的位置。 医生办公室(11)和家电制造设施(13)之间的交互式计算机连接允许正牙医(14)控制病人的拱形并修改建议的计算机确定的六个自由度的牙齿位置和方位, 并尝试新的位置,提取,过度校正和其他变化,计算机以高精度重新计算牙齿位置以批准正牙医生。 该设备根据最终设计自动设计,也可以由正牙医生进行交互式修改和批准,计算机会重新计算由于医生改变而对治疗的影响。 支架(81)通过在其中切割槽或者通过例如立体光刻在层中构建托架来制造为一体的集合。 自动制作三维定制夹具(87),将支架精确定位在患者牙齿上。