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    Method for Display of Pre-Rendered Computer Aided Diagnosis Results
    41.
    发明申请
    Method for Display of Pre-Rendered Computer Aided Diagnosis Results 审中-公开
    显示预渲染计算机辅助诊断结果的方法

    公开(公告)号：US20090309874A1

    公开(公告)日：2009-12-17

    申请号：US12420430

    申请日：2009-04-08

    申请人： Marcos Salganicoff ,  Arun Krishnan ,  Sarang Lakare

    发明人： Marcos Salganicoff ,  Arun Krishnan ,  Sarang Lakare

    IPC分类号： G06T15/00

    CPC分类号： G06T19/00 ,  A61B6/463 ,  A61B6/466 ,  A61B6/5217 ,  A61B6/563 ,  G06F19/321 ,  G06T2210/41

    摘要： A method for displaying pre-rendered medical images on a workstation includes receiving three-dimensional medical image data. A region of suspicion is automatically identified within the three-dimensional medical image data. A rendering workstation is used to pre-render the three-dimensional medical image data into a sequence of two-dimensional images in which the identified region of suspicion is featured from a vantage point that is automatically selected to maximize diagnostic value of the two-dimensional images for determining whether the region of suspicion is an actual abnormality. The sequence of pre-rendered two-dimensional images is then stored in a PACS, where it can then be displayed on a viewing workstation.

    摘要翻译： 一种用于在工作站上显示预先呈现的医学图像的方法包括接收三维医学图像数据。 在三维医学图像数据内自动识别怀疑区域。 渲染工作站用于将三维医学图像数据预渲染成二维图像序列，其中所识别的怀疑区域的特征在于自动选择的有利位置以最大化二维的诊断价值 用于确定怀疑区域是否是实际异常的图像。 然后将预渲染的二维图像的序列存储在PACS中，然后可以将其显示在观看工作站上。

    Method and system for detection and registration of 3D objects using incremental parameter learning
    42.
    发明申请
    Method and system for detection and registration of 3D objects using incremental parameter learning 有权
    使用增量参数学习检测和注册3D对象的方法和系统

    公开(公告)号：US20080211812A1

    公开(公告)日：2008-09-04

    申请号：US12012386

    申请日：2008-02-01

    申请人： Adrian Barbu ,  Le Lu ,  Luca Bogoni ,  Marcos Salganicoff ,  Dorin Comaniciu

    发明人： Adrian Barbu ,  Le Lu ,  Luca Bogoni ,  Marcos Salganicoff ,  Dorin Comaniciu

    IPC分类号： G06T17/00 ,  G06K9/00

    CPC分类号： G06K9/32 ,  G06K9/00201 ,  G06K9/6256 ,  G06K2209/051

    摘要： A method and system for detecting 3D objects in images is disclosed. In particular, a method and system for Ileo-Cecal Valve detection in 3D computed tomography (CT) images using incremental parameter learning and ICV specific prior learning is disclosed. First, second, and third classifiers are sequentially trained to detect candidates for position, scale, and orientation parameters of a box that bounds an object in 3D image. In the training of each sequential classifier, new training samples are generated by scanning the object's configuration parameters in the current learning projected subspace (position, scale, orientation), based on detected candidates resulting from the previous training step. This allows simultaneous detection and registration of a 3D object with full 9 degrees of freedom. ICV specific prior learning can be used to detect candidate voxels for an orifice of the ICV and to detect initial ICV box candidates using a constrained orientation alignment at each candidate voxel.

    摘要翻译： 公开了一种用于检测图像中的3D物体的方法和系统。 特别地，公开了使用增量参数学习和ICV特有的先前学习的3D计算机断层摄影（CT）图像中Ileo-Cecal Valve检测的方法和系统。 顺序训练第一，第二和第三分类器以检测在3D图像中界定对象的框的位置，缩放和取向参数的候选。 在每个顺序分类器的训练中，基于从先前训练步骤产生的检测到的候选，通过在当前学习投影子空间（位置，比例，方向）中扫描对象的配置参数来生成新的训练样本。 这允许同时检测和注册具有全9自由度的3D对象。 ICV具体的先验学习可用于检测ICV孔口的候选体素，并使用每个候选体素上的约束取向对齐来检测初始ICV盒候选。

    Method for Detection and Visional Enhancement of Blood Vessels and Pulmonary Emboli
    43.
    发明申请
    Method for Detection and Visional Enhancement of Blood Vessels and Pulmonary Emboli 有权
    血管和肺栓塞的检测和视觉增强方法

    公开(公告)号：US20080050003A1

    公开(公告)日：2008-02-28

    申请号：US11841168

    申请日：2007-08-20

    申请人： Senthil Periaswamy ,  Marcos Salganicoff

    发明人： Senthil Periaswamy ,  Marcos Salganicoff

    IPC分类号： G06K9/00

    CPC分类号： G06T7/0012 ,  G06K9/4609 ,  G06K2209/05 ,  G06T5/50 ,  G06T7/12 ,  G06T2207/10072 ,  G06T2207/10116 ,  G06T2207/30061 ,  G06T2207/30101

    摘要： A method for detecting a substantially cylindrical internal structures and dark structures surrounded by bright intensity values (contrast) in a medical image includes acquiring a medical image. A gradient of the medical image is calculated. Local shape index information for the calculated gradient of the medical image is calculated. Gradient information having a local shape index not indicative of a ridge and rut shapes is removed. Diverging gradient field responses (DGFR) are calculated based on the remaining gradient information. The DGFR responses and relative amount of DGFR responses for the rut and ridge areas is used as a discriminative feature in detecting the substantially cylindrical internal structure as well as darker occluding structures within cylindrical structures such as Pulmonary Emboli.

    摘要翻译： 用于检测医疗图像中由亮度值（对比度）包围的基本上圆柱形的内部结构和暗结构的方法包括获取医学图像。 计算医学图像的梯度。 计算医学图像的计算梯度的局部形状指数信息。 具有不表示脊和车辙形状的局部形状指标的梯度信息被去除。 基于剩余梯度信息计算发散梯度场响应（DGFR）。 用于车辙和脊部区域的DGFR响应和DGFR响应的相对量用作检测圆柱形结构（例如肺栓塞）中的基本上圆柱形的内部结构以及较暗的闭塞结构的鉴别特征。