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126 条记录 (耗时 0.042 秒)

    OXYGEN SEPARATION ASSEMBLY AND METHOD
    1.
    发明申请
    OXYGEN SEPARATION ASSEMBLY AND METHOD 审中-公开
    氧分离装置和方法

    公开(公告)号：US20100116133A1

    公开(公告)日：2010-05-13

    申请号：US12267801

    申请日：2008-11-10

    申请人： David M. Reed ,  David Suggs ,  Michael J. Collins ,  Richard Kelly ,  Gervase M. Christie

    发明人： David M. Reed ,  David Suggs ,  Michael J. Collins ,  Richard Kelly ,  Gervase M. Christie

    IPC分类号： B03C3/06

    CPC分类号： C01B13/0255 ,  B01D53/326 ,  B01D2053/223 ,  B01D2256/12 ,  B01D2257/104 ,  B01D2258/06 ,  C01B2210/0046

    摘要： The present invention provides an electrically driven oxygen separation assembly and method of applying an electrical potential thereto in which one or more tubular membrane elements are provided having an anode layer, a cathode layer, an electrolyte layer and two current collector layers adjacent to and in contact with the anode layer and the cathode layer and situated on the inside and outside of the at least one tubular membrane element. The potential is applied to one of the two current collector layers at two central spaced locations of the at least one tubular membrane element and to the other of the two current collector layers at least at opposite end locations thereof. As a result the electric current flow through the tubular membrane element is divided into two parts flowing between the two central spaced locations and the opposite end locations.

    摘要翻译： 本发明提供一种电驱动氧分离组件及其电位施加方法，其中提供一个或多个管状膜元件，其中阳极层，阴极层，电解质层和邻近和接触的两个集电器层 与阳极层和阴极层并且位于至少一个管状膜元件的内部和外部。 在至少一个管状膜元件的两个中心间隔位置处并且至少在两个集电器层中的另一个至少在其相对的端部位置处将电位施加到两个集电器层中的一个。 结果，流过管状膜元件的电流被分成在两个中心间隔位置和相对端部位置之间流动的两个部分。

    Automated lesion characterization
    5.
    发明授权
    Automated lesion characterization 有权

    公开(公告)号：US07787682B2

    公开(公告)日：2010-08-31

    申请号：US12573324

    申请日：2009-10-05

    申请人： Michael J. Collins ,  Daniel Corwin-Renner

    发明人： Michael J. Collins ,  Daniel Corwin-Renner

    IPC分类号： G06K9/00

    CPC分类号： G06T7/0012 ,  A61B6/502 ,  G06T2207/30068

    摘要： A method and system that provides users with additional information regarding imagery analyzed by computer-aided detection (CAD) systems is described. A user selects a region of the analyzed imagery. Information is then derived from computational measurements of the region obtained during CAD processing. The region selected by the user does not necessarily have to include a displayed CAD system detection. The information includes a description of the computational measurement and the value of the measurement, both of which are provided in clinically relevant terms.

    COMPUTER-AIDED DETECTION AND CLASSIFICATION OF SUSPICIOUS MASSES IN BREAST IMAGERY
    6.
    发明申请
    COMPUTER-AIDED DETECTION AND CLASSIFICATION OF SUSPICIOUS MASSES IN BREAST IMAGERY 有权
    乳腺成像中计算机辅助检测和分类的可疑质量

    公开(公告)号：US20100067754A1

    公开(公告)日：2010-03-18

    申请号：US12211593

    申请日：2008-09-16

    申请人： Michael J. Collins ,  Kevin Woods ,  Brent Woods ,  William Pierson ,  Ryan McGinnis

    发明人： Michael J. Collins ,  Kevin Woods ,  Brent Woods ,  William Pierson ,  Ryan McGinnis

    IPC分类号： G06K9/00 ,  G06K9/62

    CPC分类号： G06K9/6292 ,  G06K2209/053 ,  G06T7/0012 ,  G06T2207/30068

    摘要： Methods, a system, and a computer readable medium are presented that detect and classify mass-like regions exhibiting spiculated and/or dense characteristics with high sensitivity and at acceptable false positive rates. One or more suspicious masses are identified in medical imagery of the breast. In accordance with certain embodiments, for each suspicious mass located, a quantitative measure of spiculation and quantitative measure of density are computed. At least one classification scheme is then selected for each suspicious mass according to both quantitative measures. Each classification scheme is developed using true positives and false positives with similar quantitative measures.In accordance with certain other embodiments, for each suspicious mass located, a measure of breast location is computed. At least one classification scheme is then selected for each suspicious mass according to the measure of breast location. Each classification scheme is developed using true positives and false positives that appear in the same breast location. In one embodiment, the location measure determines whether a suspicious mass appears inside or outside of the parenchyma region of the breast.

    摘要翻译： 提出了方法，系统和计算机可读介质，其以高灵敏度和可接受的假阳性率检测和分类显示具有螺旋和/或密度特征的质量样区域。 在乳房的医学图像中识别出一个或多个可疑群体。 根据某些实施例，对于每个可疑的质量位置，计算密度的定量测量和密度的定量测量。 然后根据这两种量化措施，为每个可疑物质选择至少一种分类方案。 每个分类方案是使用具有相似量化措施的真阳性和假阳性来开发的。 根据某些其他实施例，对于位于每个可疑质量块，计算乳房位置的量度。 然后根据乳房位置的测量，为每个可疑质量选择至少一个分类方案。 每个分类方案使用出现在同一乳房位置的真阳性和假阳性进行开发。 在一个实施例中，位置测量确定可疑质量是否出现在乳房的实质区域的内部或外部。

    Multiple image fusion
    8.
    发明授权
    Multiple image fusion 有权
    多重图像融合

    公开(公告)号：US07333645B1

    公开(公告)日：2008-02-19

    申请号：US10973837

    申请日：2004-10-26

    申请人： Richard A. Mitchell ,  Michael J. Collins

    发明人： Richard A. Mitchell ,  Michael J. Collins

    IPC分类号： G06K9/00

    CPC分类号： G06K9/3233 ,  G06K2209/053 ,  G06T7/0012 ,  G06T2207/10116 ,  G06T2207/30068 ,  Y10S128/92 ,  Y10S128/922

    摘要： The method and system for exploiting information from multiple images in a mammographic computer-aided detection application is disclosed. A pair of images is obtained by a CAD system. The images are processed to produce a set of regions of interest (ROIs) to be associated with each image. A ROI is selected from the first image of the pair. This ROI is identified and matched to a ROI in the second image. The single image feature values are obtained by the two ROIs of the image pair. Transforming the image feature value to an integer value produces a pair of integers for each image feature value. The pair of integers defines the element of the pre-determined co-occurrence matrix. An element of a predetermined co-occurrence matrix is selected to provide evidence value for the ROI of the first image.

    摘要翻译： 公开了一种在乳房X光计算机辅助检测应用中利用来自多个图像的信息的方法和系统。 通过CAD系统获得一对图像。 处理图像以产生要与每个图像相关联的一组感兴趣区域（ROI）。 从该对的第一个图像中选择ROI。 该ROI被识别并与第二图像中的ROI匹配。 单个图像特征值由图像对的两个ROI获得。 将图像特征值转换为整数值可为每个图像特征值生成一对整数。 这对整数定义了预先确定的同现矩阵的元素。 选择预定同现矩阵的元素以提供第一图像的ROI的证据值。

    Dual Energy Source Loss-On-Drying Instrument
    9.
    发明申请
    Dual Energy Source Loss-On-Drying Instrument 有权
    双能量损耗干燥仪

    公开(公告)号：US20080013592A1

    公开(公告)日：2008-01-17

    申请号：US11457798

    申请日：2006-07-15

    申请人： Robert N. Revesz ,  Michael J. Collins

    发明人： Robert N. Revesz ,  Michael J. Collins

    IPC分类号： G01N25/00

    CPC分类号： G01N5/045 ,  G01N1/44

    摘要： An instrument and associated method are disclosed for the loss-on-drying determination of the volatile content of a wide variety of samples. The instrument includes a cavity in which a sample for which the volatile content is to be determined can be placed, a first source for introducing microwaves into the cavity that have frequencies substantially other than infrared frequencies, a second source for introducing radiant heat into the cavity at frequencies different from the frequencies introduced by the first source, an analytical balance for measuring the weight of a sample while the sample is in the cavity and on the balance, a temperature sensor capable of measuring and positioned to measure the temperature of a sample in the cavity and on the balance, and a processor in communication with the temperature sensor and each of the first and second sources for controlling the introduction of the frequencies of microwave and radiant energy into the cavity in response to the temperatures measured by the temperature sensor to control the sample temperature until the microwaves from the first source and the radiant heat from the second source dry the sample sufficiently for the processor to determine the volatile content of the sample based on the weight change of the sample on the balance.

    摘要翻译： 公开了用于各种样品的挥发物含量的干燥损失测定的仪器和相关方法。 该仪器包括其中可以放置要确定挥发物含量的样品的空腔，用于将微波引入具有基本上不同于红外频率的频率的空腔的第一源，用于将辐射热引入腔中的第二源 在与第一源引入的频率不同的频率处，用于测量样品在腔中和平衡时的重量的分析天平，能够测量和定位以测量样品的温度的温度传感器 空腔和平衡部，以及与温度传感器和第一和第二源中的每一个通信的处理器，用于响应于由温度传感器测量的温度而将微波和辐射能的频率引入腔中 控制样品温度，直到来自第一个来源的微波和来自th的辐射热 第二来源充分干燥样品以使处理器基于样品在天平上的重量变化来确定样品的挥发性含量。

    Method for analyzing detections in a set of digital images using case based normalcy classification
    10.
    发明授权
    Method for analyzing detections in a set of digital images using case based normalcy classification 有权
    使用基于案例的正常分类来分析一组数字图像中的检测的方法

    公开(公告)号：US06763128B1

    公开(公告)日：2004-07-13

    申请号：US10461316

    申请日：2003-06-13

    申请人： Steven K. Rogers ,  Michael J. Collins ,  Richard A. Mitchell

    发明人： Steven K. Rogers ,  Michael J. Collins ,  Richard A. Mitchell

    IPC分类号： B06K900

    CPC分类号： G06K9/6293 ,  G06K9/4609 ,  G06K9/56 ,  G06K2209/05 ,  G06T7/0012 ,  G06T2207/30068

    摘要： A computer aided detection method and system to assist radiologists in the reading of medical images. The method and system has particular application to the area of mammography including detection of clustered microcalcifications and densities. A microcalcification detector is provided wherein individual detections are rank ordered and classified, and one of the features for classification is derived using a multilayer perceptron. A density detector is provided including an iterative, dynamic region growing module with embedded subsystem for rank ordering and classification of a best subset of candidate masks. A post processing stage is provided where detections are analyzed in the context of a set of images for a patient. The post processing includes a normalcy classification including providing computed values corresponding to each detection from a category of detections on an image set, computing a normalcy value using the computed values, and removing all detections from an image set when the normalcy value does not meet a predetermined condition. The final output of the system is a set of indications overlaid on the input medical images.

    摘要翻译： 一种计算机辅助检测方法和系统，用于帮助放射科医师阅读医学图像。 该方法和系统在乳腺摄影领域具有特殊应用，包括检测聚类微钙化和密度。 提供了一种微钙化检测器，其中单独的检测是排序和分类的，并且使用多层感知器导出用于分类的特征之一。 提供了一种密度检测器，其包括具有嵌入式子系统的迭代动态区域增长模块，用于对候选掩模的最佳子集进行排序和分类。 提供后处理阶段，其中在用于患者的一组图像的上下文中分析检测。 后处理包括正常分类，包括从图像集中的检测类别提供与每个检测相对应的计算值，使用计算值计算正常值，以及当正常值不满足时从图像集中移除所有检测 预定条件。 系统的最终输出是覆盖在输入医学图像上的一组指示。