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105 条记录 (耗时 0.025 秒)

    Method and system for detection and tracking of coronary sinus catheter electrodes in fluoroscopic images
    41.
    发明授权
    Method and system for detection and tracking of coronary sinus catheter electrodes in fluoroscopic images 有权
    荧光镜检查和跟踪冠状静脉窦导管电极的方法和系统

    公开(公告)号：US08892186B2

    公开(公告)日：2014-11-18

    申请号：US13229855

    申请日：2011-09-12

    申请人： Wen Wu ,  Terrence Chen ,  Peng Wang ,  Norbert Strobel ,  Shaohua Kevin Zhou ,  Dorin Comaniciu

    发明人： Wen Wu ,  Terrence Chen ,  Peng Wang ,  Norbert Strobel ,  Shaohua Kevin Zhou ,  Dorin Comaniciu

    IPC分类号： A61B5/05 ,  G06T7/00 ,  G06T7/20 ,  A61B19/00

    CPC分类号： G06T7/0014 ,  A61B2034/2065 ,  A61B2090/376 ,  G06K2209/057 ,  G06T7/20 ,  G06T2207/10121 ,  G06T2207/30021 ,  G06T2207/30048

    摘要： A method and system for detecting and tracking coronary sinus (CS) catheter electrodes in a fluoroscopic image sequence is disclosed. An electrode model is initialized in a first frame of the fluoroscopic image sequence based on input locations of CS sinus catheter electrodes in the first frame. The electrode model is tracked in subsequent frames of the fluoroscopic image sequence by detecting electrode position candidates in the subsequent frames of the fluoroscopic image sequence using at least one trained electrode detector, generating electrode model candidates in the subsequent frames based on the detected electrode position candidates, calculating a probability score for each of the electrode model candidates, and selecting an electrode model candidate based on the probability score.

    摘要翻译： 公开了一种用于在荧光镜图像序列中检测和跟踪冠状窦（CS）导管电极的方法和系统。 基于第一帧中的CS窦导管电极的输入位置，在荧光镜图像序列的第一帧中初始化电极模型。 通过使用至少一个经过训练的电极检测器检测荧光镜像图像序列的后续帧中的电极位置候选物，在荧光图像序列的后续帧中跟踪电极模型，基于检测到的电极位置候选产生后续帧中的电极模型候选 计算每个电极模型候选的概率分数，并且基于概率分数来选择电极模型候选。

    Method and System for Efficient Extraction of a Silhouette of a 3D Mesh
    44.
    发明申请
    Method and System for Efficient Extraction of a Silhouette of a 3D Mesh 有权
    一种3D网格剪影效率提取的方法与系统

    公开(公告)号：US20120069017A1

    公开(公告)日：2012-03-22

    申请号：US13235802

    申请日：2011-09-19

    申请人： Yefeng Zheng ,  Yu Pang ,  Rui Liao ,  Matthias John ,  Jan Boese ,  Shaohua Kevin Zhou ,  Dorin Comaniciu

    发明人： Yefeng Zheng ,  Yu Pang ,  Rui Liao ,  Matthias John ,  Jan Boese ,  Shaohua Kevin Zhou ,  Dorin Comaniciu

    IPC分类号： G06T17/00

    CPC分类号： G06T17/20 ,  G06T7/12 ,  G06T7/181

    摘要： A method and system for extracting a silhouette of a 3D mesh representing an anatomical structure is disclosed. The 3D mesh is projected to two dimensions. Silhouette candidate edges are generated in the projected mesh by pruning edges and mesh points based on topology analysis of the projected mesh. Each silhouette candidate edge that intersects with another edge in the projected mesh is split into two silhouette candidate edges. The silhouette is extracted using an edge following process on the silhouette candidate edges.

    摘要翻译： 公开了一种用于提取表示解剖结构的3D网格的轮廓的方法和系统。 3D网格投影到两个维度。 通过基于投影网格的拓扑分析修剪边缘和网格点，在投影网格中生成剪影候选边缘。 与投影网格中的另一边缘相交的每个剪影候选边缘被分割成两个轮廓候选边缘。 使用轮廓候选边缘上的边缘跟随过程提取轮廓。

    Data Transmission in Remote Computer Assisted Detection
    45.
    发明申请
    Data Transmission in Remote Computer Assisted Detection 有权
    远程计算机辅助检测中的数据传输

    公开(公告)号：US20110243407A1

    公开(公告)日：2011-10-06

    申请号：US13080891

    申请日：2011-04-06

    申请人： Michal Sofka ,  Kristof Ralovich ,  Jingdan Zhang ,  Shaohua Kevin Zhou ,  Gianluca Paladini ,  Dorin Comaniciu

    发明人： Michal Sofka ,  Kristof Ralovich ,  Jingdan Zhang ,  Shaohua Kevin Zhou ,  Gianluca Paladini ,  Dorin Comaniciu

    IPC分类号： G06K9/46 ,  G06K9/36 ,  G06K9/00

    CPC分类号： G06K9/6256 ,  G06F19/00 ,  G06F19/321 ,  G06T7/0012 ,  G06T2200/16 ,  G06T2207/20016

    摘要： For cloud-based computer assisted detection, hierarchal detection is used, allowing detection on data at progressively greater resolutions. Detected locations at coarser resolutions are used to limit the data transmitted at greater resolutions. Data is only transmitted for neighborhoods around the previously detected locations. Subsequent detection using higher resolution data refines the locations, but only for regions associated with previous detection. By limiting the number and/or size of regions provided at greater resolutions based on the previous detection, the progressive transmission avoids transmission of some data. Additionally, or alternatively, lossy compression may be used without or with minimal reduction in detection sensitivity.

    摘要翻译： 对于基于云的计算机辅助检测，使用层次检测，允许以逐渐更大的分辨率检测数据。 较粗分辨率下的检测位置用于限制以更高分辨率传输的数据。 仅针对先前检测到的位置周围的邻域发送数据。 使用较高分辨率数据的后续检测会优化位置，但仅适用于与先前检测相关的区域。 通过基于先前的检测限制以更大分辨率提供的区域的数量和/或尺寸，逐行传输避免了一些数据的传输。 另外或者可选地，可以使用有损压缩，而不用或以最小的检测灵敏度降低。

    Method and system for learning based object detection in medical images
    48.
    发明授权
    Method and system for learning based object detection in medical images 有权
    医学图像学习基于物体检测的方法与系统

    公开(公告)号：US08737725B2

    公开(公告)日：2014-05-27

    申请号：US13235747

    申请日：2011-09-19

    申请人： Peng Wang ,  Terrence Chen ,  Shaohua Kevin Zhou ,  Dorin Comaniciu ,  Martin Ostermeier

    发明人： Peng Wang ,  Terrence Chen ,  Shaohua Kevin Zhou ,  Dorin Comaniciu ,  Martin Ostermeier

    IPC分类号： G06K9/62

    CPC分类号： G06K9/4614 ,  G06K9/6257 ,  G06K9/6282

    摘要： Methods and Systems for training a learning based classifier and object detection in medical images is disclosed. In order to train a learning based classifier, positive training samples and negative training samples are generated based on annotated training images. Features for the positive training samples and the negative training samples are extracted. The features include an extended Haar feature set including tip features and corner features. A discriminative classifier is trained based on the extracted features.

    摘要翻译： 公开了用于训练医学图像中基于学习的分类器和对象检测的方法和系统。 为了训练基于学习的分类器，基于注释的训练图像生成正训练样本和负训练样本。 提取正训练样本和负训练样本的特征。 功能包括扩展的Haar功能集，包括提示功能和角特征。 基于提取的特征对歧视性分类器进行训练。