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    Methods of providing graphics data and displaying
    13.
    发明授权
    Methods of providing graphics data and displaying 有权
    提供图形数据和显示的方法

    公开(公告)号：US09064350B2

    公开(公告)日：2015-06-23

    申请号：US12669382

    申请日：2007-07-18

    Applicant: Hock Soon Seah ,  Feng Tian ,  Yixiang Lu ,  Jie Qiu ,  Quan Chen ,  Peng Lu

    Inventor： Hock Soon Seah ,  Feng Tian ,  Yixiang Lu ,  Jie Qiu ,  Quan Chen ,  Peng Lu

    IPC: G06T13/00 ,  G09G5/00 ,  G06T1/00 ,  G06T13/80 ,  G06T9/00

    CPC classification number: G06T13/80 ,  G06T9/00 ,  G06T2200/16 ,  G06T2210/08

    Abstract: A method of providing graphics data, comprising generating a first set of data vectors specifying geometrical characteristics of a graphical object in a first digital picture, generating a second set of data vectors specifying geometrical characteristics of the graphical object in a second digital picture to be displayed after the first digital picture, generating a parameter set comprising information specifying intermediate geometrical characteristics of the graphical object based on the geometrical characteristics of the graphical object in the first digital picture, and of the graphical object in the second digital picture, wherein the intermediate geometrical characteristics are geometrical characteristics of the graphical object in at least one third digital picture to be displayed after the first digital picture and before the second digital picture, and generating at least one data file comprising the first set of data vectors, the second set of data vectors and the parameter set.

    Abstract translation: 一种提供图形数据的方法，包括生成指定第一数字图像中的图形对象的几何特征的第一组数据向量，产生指定要显示的第二数字图像中的图形对象的几何特征的第二组数据向量 在第一数字图像之后，基于第一数字图像中的图形对象的几何特征和第二数字图像中的图形对象，生成包括指定图形对象的中间几何特征的信息的参数集，其中中间几何 特征是在要在第一数字图像之后和第二数字图像之前显示的至少一个第三数字图像中的图形对象的几何特征，并且生成包括第一组数据矢量的至少一个数据文件，第二组数据 向量和参数s 等。

    Method for molding semiconductor device
    14.
    发明授权
    Method for molding semiconductor device 有权
    半导体器件成型方法

    公开(公告)号：US08652384B2

    公开(公告)日：2014-02-18

    申请号：US13489466

    申请日：2012-06-06

    Applicant: Quan Chen ,  Wei Gai ,  Yanbo Xu

    Inventor： Quan Chen ,  Wei Gai ,  Yanbo Xu

    IPC: B29C45/14

    CPC classification number: H01L21/565 ,  H01L2924/0002 ,  H01L2924/00

    Abstract: An apparatus for molding a semiconductor device includes an upper mold chase and a lower mold chase. The mold chases are capable of being aligned with each other, forming spaced cavities for receiving a lead frame array that includes semiconductor dies for encapsulation. The cavities are aligned in spaced, vertical columns and gates are provided at the opening of each column of cavities. A molding compound is passed through the gates and flows uninterrupted through each cavity and encapsulates the semiconductor dies.

    Abstract translation: 用于模制半导体器件的设备包括上模追逐和下模追逐。 模具能够彼此对准，形成间隔开的空腔，用于接收包括用于封装的半导体管芯的引线框架阵列。 空腔以间隔开的垂直柱对准，并且在每个空腔列的开口处提供浇口。 模制化合物通过栅极并且不间断地流过每个空腔并封装半导体管芯。

    Methods for supporting rapid network topology changes with low overhead costs and devices of the same
    16.
    发明授权
    Methods for supporting rapid network topology changes with low overhead costs and devices of the same 有权
    支持快速网络拓扑变化的方法，具有低开销成本和相同的设备

    公开(公告)号：US08462650B2

    公开(公告)日：2013-06-11

    申请号：US12581113

    申请日：2009-10-16

    Applicant: Gang Qiang ,  Yang Zhang ,  Quan Chen ,  Xiao Ming Lan ,  Peng Li

    Inventor： Gang Qiang ,  Yang Zhang ,  Quan Chen ,  Xiao Ming Lan ,  Peng Li

    IPC: G01R31/08 ,  G06F11/00 ,  G08C15/00 ,  H04J1/16 ,  H04J3/14 ,  H04L1/00 ,  H04L12/26

    CPC classification number: H04W40/20 ,  H04L45/123

    Abstract: The present invention discloses a wireless communication method of supporting rapid changes in network topology. The present method may include broadcasting the first protocol message using the first broadcast cycle, the first protocol message being used for establishing a routing information between a node and destination node; and broadcasting the second protocol message using the second broadcast cycle, the second protocol message being used for establishing a link information between the node and a neighbor node, wherein the first broadcast cycle is different from the second broadcast cycle, and the first broadcast cycle is dynamically adjusted depending on a corresponding a detailed message contained in a plurality of segments in the first protocol message so as to reduce a number of broadcast of the first protocol message.

    Abstract translation: 本发明公开了一种支持网络拓扑快速变化的无线通信方法。 本方法可以包括使用第一广播周期广播第一协议消息，第一协议消息用于在节点和目的节点之间建立路由信息; 以及使用所述第二广播周期广播所述第二协议消息，所述第二协议消息用于在所述节点和邻居节点之间建立链路信息，其中所述第一广播周期不同于所述第二广播周期，并且所述第一广播周期是 根据包含在第一协议消息中的多个段中的相应的详细消息来动态地调整，以便减少第一协议消息的广播数量。

    NON-VOXEL-BASED BROAD-BEAM (NVBB) ALGORITHM FOR INTENSITY MODULATED RADIATION THERAPY DOSE CALCULATION AND PLAN OPTIMIZATION
    17.
    发明申请
    NON-VOXEL-BASED BROAD-BEAM (NVBB) ALGORITHM FOR INTENSITY MODULATED RADIATION THERAPY DOSE CALCULATION AND PLAN OPTIMIZATION 有权
    用于强度调制辐射治疗剂量计算和计划优化的非基于VOXEL的BROAD-BEAM（NVBB）算法

    公开(公告)号：US20110122997A1

    公开(公告)日：2011-05-26

    申请号：US12915618

    申请日：2010-10-29

    Applicant: Weiguo Lu ,  Mingli Chen ,  Quan Chen ,  Kenneth J. Ruchala

    Inventor： Weiguo Lu ,  Mingli Chen ,  Quan Chen ,  Kenneth J. Ruchala

    IPC: A61N5/10

    CPC classification number: A61N5/1031 ,  A61N5/1042 ,  A61N5/1045

    Abstract: A method of calculating a dose distribution for a patient for use in a radiation therapy treatment plan. The method includes acquiring an image of a volume within the patient, defining a radiation source, and defining a reference plane oriented between the radiation source and the patient. The method also includes generating a radiation therapy treatment plan, wherein the plan includes a plurality of rays that extend between the radiation source and the patient volume, and calculating a three-dimensional dose volume for the patient volume from the plurality of rays that intersect the reference plane without first having to independently calculate a dose distribution on each of the plurality of rays. The method can also include displaying the three-dimensional dose volume.

    Abstract translation: 计算用于放射治疗治疗计划中的患者的剂量分布的方法。 该方法包括获取患者体内的体积的图像，限定辐射源，以及定义在辐射源和患者之间定向的参考平面。 该方法还包括产生放射治疗治疗计划，其中该计划包括在辐射源和患者体积之间延伸的多条射线，以及从与所述辐射源和患者体积相交的多个射线计算患者体积的三维剂量体积 不必首先必须独立地计算多个光线中的每一个上的剂量分布。 该方法还可以包括显示三维剂量体积。

    Systems and methods for automatic segmentation of organs from head and neck tomographic images
    19.
    发明授权
    Systems and methods for automatic segmentation of organs from head and neck tomographic images 有权

    公开(公告)号：US12039735B2

    公开(公告)日：2024-07-16

    申请号：US17529188

    申请日：2021-11-17

    Applicant: Xue Feng ,  Quan Chen ,  Kanchan Ghimire

    Inventor： Xue Feng ,  Quan Chen ,  Kanchan Ghimire

    IPC: G06T7/168

    CPC classification number: G06T7/168 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20216 ,  G06T2207/30004

    Abstract: The present disclosure relates to a method and apparatus for automatic head and neck organ segmentation. The method includes: prepare a training dataset, wherein the step of preparing a training dataset comprises: receive 3D images covering head and neck region obtained by a CT system or an MRI system; receive metadata for each received 3D images, comprising patient orientation, pixel spacing, slice thickness and matrix size; receive corresponding 3D segmentation labels map for the received 3D images; and process the received 3D images and the corresponding 3D segmentation labels map by transforming to patient coordinate system and resampling to have a fixed spatial resolution and a fixed matrix size; build a deep learning framework using CNN models for organ segmentation; train CNN models using the training dataset and performing data emulation step during training by mirroring the processed 3D images and their corresponding processed 3D segmentation labels map from the training dataset; prepare a testing dataset, wherein the step of preparing a testing dataset comprises: receive 3D images covering head and neck region obtained by a CT system or an MRI system; receive metadata for each received 3D images, comprising patient orientation, pixel spacing, slice thickness and matrix size; and process the received 3D images by transforming to patient coordinate system and resampling to have a fixed spatial resolution and a fixed matrix size; deploy the trained CNN models on testing dataset, wherein the testing step comprises: mirror the processed 3D images in the left-right direction; predict on the processed 3D images and mirrored 3D images with individual prediction outputs as 3D probabilities map for organ segmentation; and improve the segmentation performance by averaging the 3D probabilities map outputs from the processed 3D images and mirrored 3D images; and post-process the 3D probabilities map outputs from the deep learning framework to obtain final 3D segmentation labels map for organ segmentation.

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