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81. 发明授权

US08194955B2 Method and system for detection of contrast injection in fluoroscopic image sequences 有权
标题翻译：荧光图像序列中对比度注入检测方法和系统
公开(公告)号：US08194955B2
公开(公告)日：2012-06-05
申请号：US12231770
申请日：2008-09-05
申请人： Benjamin J. Sapp , Wei Zhang , Bogdan Georgescu , Simone Prummer , Dorin Comaniciu
发明人： Benjamin J. Sapp , Wei Zhang , Bogdan Georgescu , Simone Prummer , Dorin Comaniciu
IPC分类号： G06K9/00
CPC分类号： G06K9/00 , G06K2209/05 , G06T7/0012
摘要： A method and system for detecting a spatial and temporal location of a contrast injection in a fluoroscopic image sequence is disclosed. Training volumes generated by stacking a sequence of 2D fluoroscopic images in time order are annotated with ground truth contrast injection points. A heart rate is globally estimated for each training volume, and local frequency and phase is estimated in a neighborhood of the ground truth contrast injection point for each training volume. Frequency and phase invariant features are extracted from each training volume based on the heart rate, local frequency and phase, and a detector is trained based on the training volumes and the features extracted for each training volume. The detector can be used to detect the spatial and temporal location of a contrast injection in a fluoroscopic image sequence.
摘要翻译：公开了一种用于检测透视图像序列中的对比度注入的空间和时间位置的方法和系统。通过以时间顺序堆叠一系列2D透视图像而产生的训练体积用地面真实对比度注入点注释。对于每个训练体积，全局估计心率，并且在每个训练体积的地面真实对比度注入点的邻域中估计局部频率和相位。基于心率，局部频率和相位从每个训练体积中提取频率和相位不变特征，并且基于训练量和针对每个训练体积提取的特征来训练检测器。检测器可用于检测透视图像序列中对比度注入的空间和时间位置。

82. 发明申请

US20120134564A1 Method and System for Heart Isolation in Cardiac Computed Tomography Volumes for Patients with Coronary Artery Bypasses 有权
标题翻译：心脏计算机断层摄影术心脏隔离方法与系统用于冠状动脉旁路术患者
公开(公告)号：US20120134564A1
公开(公告)日：2012-05-31
申请号：US13295217
申请日：2011-11-14
申请人： Yefeng Zheng , Fernando Vega-Higuera , Dorin Comaniciu
发明人： Yefeng Zheng , Fernando Vega-Higuera , Dorin Comaniciu
IPC分类号： G06K9/00
CPC分类号： G06T7/149 , G06T7/11 , G06T2207/10081 , G06T2207/20124 , G06T2207/30048
摘要： A method and system for isolating the heart in a 3D volume, such as a cardiac CT volume, for patients with coronary artery bypasses is disclosed. An initial heart isolation mask is extracted from a 3D volume, such as a cardiac CT volume. The aortic root and ascending aorta are segmented in the 3D volume, resulting in an aorta mesh. The aorta mesh is expanded to include bypass coronary arteries. An expanded heart isolation mask is generated by combining the initial heart isolation mask with an expanded aorta mask defined by the expanded aorta mesh.
摘要翻译：公开了一种用于分离冠状动脉旁路患者的3D体积（例如心脏CT体积）中的心脏的方法和系统。从3D体积（例如心脏CT体积）提取初始心脏隔离掩模。主动脉根部和升主动脉在3D体积中分段，导致主动脉网。主动脉网扩张包括旁路冠状动脉。通过将初始心脏隔离掩模与由扩张的主动脉网所定义的扩张主动脉掩膜组合来产生扩张的心脏隔离掩模。

83. 发明授权

US08184888B2 Method and system for polyp segmentation for 3D computed tomography colonography 有权
标题翻译：用于3D计算机断层扫描结构的息肉分割方法和系统
公开(公告)号：US08184888B2
公开(公告)日：2012-05-22
申请号：US12231772
申请日：2008-09-05
申请人： Le Lu , Adrian Barbu , Matthias Wolf , Sarang Lakare , Luca Bogoni , Marcos Salganicoff , Dorin Comaniciu
发明人： Le Lu , Adrian Barbu , Matthias Wolf , Sarang Lakare , Luca Bogoni , Marcos Salganicoff , Dorin Comaniciu
IPC分类号： G06K9/46
CPC分类号： G06T7/0012 , G06T7/11 , G06T7/143 , G06T2207/10081 , G06T2207/20076 , G06T2207/30032
摘要： A method and system for polyp segmentation in computed tomography colonogrphy (CTC) volumes is disclosed. The polyp segmentation method utilizes a three-staged probabilistic binary classification approach for automatically segmenting polyp voxels from surrounding tissue in CTC volumes. Based on an input initial polyp position, a polyp tip is detected in a CTC volume using a trained 3D point detector. A local polar coordinate system is then fit to the colon surface in the CTC volume with the origin at the detected polyp tip. Polyp interior voxels and polyp exterior voxels are detected along each axis of the local polar coordinate system using a trained 3D box. A boundary voxel is detected on each axis of the local polar coordinate system based on the detected polyp interior voxels and polyp exterior voxels by boosted 1D curve parsing using a trained classifier. This results in a segmented polyp boundary.
摘要翻译：公开了一种计算机断层扫描（CTC）体积中息肉分割的方法和系统。息肉分割方法采用三阶段概率二分类方法，自动分割CTC体积周围组织的息肉体素。基于输入的初始息肉位置，使用训练有素的3D点检测器在CTC体积中检测息肉末端。然后将局部极坐标系拟合到CTC体积中的结肠表面，其中原点在检测到的息肉末端。使用训练有素的3D框，在局部极坐标系的每个轴上检测Polyp内部体素和息肉外部体素。基于检测到的息肉内部体素和息肉外部体素，通过使用训练有素的分类器进行升压1D曲线解析，在局部极坐标系的每个轴上检测边界体素。这导致分段息肉边界。

84. 发明申请

US20120093397A1 Method and System for Learning Based Object Detection in Medical Images 有权
标题翻译：医学图像学习对象检测方法与系统
公开(公告)号：US20120093397A1
公开(公告)日：2012-04-19
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。

85. 发明授权

US08150116B2 Method and system for detection of deformable structures in medical images 有权
标题翻译：用于检测医学图像中可变形结构的方法和系统
公开(公告)号：US08150116B2
公开(公告)日：2012-04-03
申请号：US12214339
申请日：2008-06-18
申请人： Shaohua Kevin Zhou , Feng Guo , Jin-hyeong Park , Gustavo Henrique Monteiro de Barros Carneiro , Constantine Simopoulos , Joanne Otsuki , Dorin Comaniciu , John I. Jackson
发明人： Shaohua Kevin Zhou , Feng Guo , Jin-hyeong Park , Gustavo Henrique Monteiro de Barros Carneiro , Constantine Simopoulos , Joanne Otsuki , Dorin Comaniciu , John I. Jackson
IPC分类号： G06K17/00
CPC分类号： G06K9/0055 , G06K9/6206 , G06K9/6256
摘要： A method and system for detection of deformable structures in medical images is disclosed. Deformable structures can represent blood flow patterns in images such as Doppler echocardiograms. A probabilistic, hierarchical, and discriminant framework is used to detect such deformable structures. This framework integrates evidence from different primitive levels via a progressive detector hierarchy, including a series of discriminant classifiers. A target deformable structure is parameterized by a multi-dimensional parameter, and primitives or partial parameterizations of the parameter are determined. An input image is received, and a series of primitives are sequentially detected using the progressive detector hierarchy, in which each detector or classifier detects a corresponding primitive. The final detector detects configuration candidates for the deformable structure.
摘要翻译：公开了用于检测医学图像中的可变形结构的方法和系统。可变形结构可以表示图像中的血流模式，例如多普勒超声心动图。概率，分层和判别框架用于检测这种可变形结构。该框架通过渐进式检测器层次结合不同原始级别的证据，包括一系列判别分类器。目标可变形结构通过多维参数进行参数化，并确定参数的基元或部分参数化。接收输入图像，并且使用逐行检测器层级顺序地检测一系列图元，其中每个检测器或分类器检测相应的图元。最终检测器检测可变形结构的配置候选。

86. 发明授权

US08126244B2 User interface for polyp annotation, segmentation, and measurement in 3D computed tomography colonography 有权
标题翻译：用于三维计算机断层扫描结构中息肉注解，分割和测量的用户界面
公开(公告)号：US08126244B2
公开(公告)日：2012-02-28
申请号：US12231771
申请日：2008-09-05
申请人： Le Lu , Adrian Barbu , Matthias Wolf , Sarang Lakare , Luca Bogoni , Marcos Salganicoff , Dorin Comaniciu
发明人： Le Lu , Adrian Barbu , Matthias Wolf , Sarang Lakare , Luca Bogoni , Marcos Salganicoff , Dorin Comaniciu
IPC分类号： G06K9/34
CPC分类号： G16H40/63 , G06F19/00 , G06T7/0012 , G06T7/12 , G06T2200/24 , G06T2207/10072 , G06T2207/20092 , G06T2207/30032
摘要： A method and system for providing a user interface for polyp annotation, segmentation, and measurement in computer tomography colonography (CTC) volumes is disclosed. The interface receives an initial polyp position in a CTC volume, and automatically segments the polyp based on the initial polyp position. In order to segment the polyp, a polyp tip is detected in the CTC volume using a trained 3D point detector. A local polar coordinate system is then fit to the colon surface in the CTC volume with the origin at the detected polyp tip. Polyp interior voxels and polyp exterior voxels are detected along each axis of the local polar coordinate system using a trained 3D box. A boundary voxel is detected on each axis of the local polar coordinate system based on the detected polyp interior voxels and polyp exterior voxels by boosted 1D curve parsing using a trained classifier. This results in a segmented polyp boundary. The segmented polyp is displayed in the user interface, and a user can modify the segmented polyp boundary using the interface. The interface can measure the size of the segmented polyp in three dimensions. The user can also use the interface for polyp annotation in CTC volumes.
摘要翻译：公开了一种用于在计算机断层造影（CTC）体积中提供用于息肉注释，分割和测量的用户界面的方法和系统。界面在CTC体积中接收初始息肉位置，并根据初始息肉位置自动分段息肉。为了分割息肉，使用训练有素的3D点检测器在CTC体积中检测息肉末端。然后将局部极坐标系拟合到CTC体积中的结肠表面，其中原点在检测到的息肉末端。使用训练有素的3D框，在局部极坐标系的每个轴上检测Polyp内部体素和息肉外部体素。基于检测到的息肉内部体素和息肉外部体素，通过使用训练有素的分类器进行升压1D曲线解析，在局部极坐标系的每个轴上检测边界体素。这导致分段息肉边界。分段息肉显示在用户界面中，用户可以使用界面修改分段息肉边界。界面可以在三维中测量分段息肉的大小。用户还可以在CTC卷中使用界面进行息肉注释。

87. 发明授权

US08121367B2 Method and system for vessel segmentation in fluoroscopic images 有权
标题翻译：荧光镜图像中血管分割的方法和系统
公开(公告)号：US08121367B2
公开(公告)日：2012-02-21
申请号：US12229663
申请日：2008-08-26
申请人： Richard Socher , Adrian Barbu , Bogdan Georgescu , Wei Zhang , Peter Durlak , Stefan Böhm , Dorin Comaniciu
发明人： Richard Socher , Adrian Barbu , Bogdan Georgescu , Wei Zhang , Peter Durlak , Stefan Böhm , Dorin Comaniciu
IPC分类号： G06K9/00
CPC分类号： G06K9/6256 , G06K2009/00932 , G06T7/12 , G06T7/162 , G06T2207/10121 , G06T2207/30048 , G06T2207/30101
摘要： A method and system for vessel segmentation in fluoroscopic images is disclosed. Hierarchical learning-based detection is used to perform the vessel segmentation. A boundary classifier is trained and used to detect boundary pixels of a vessel in a fluoroscopic image. A cross-segment classifier is trained and used to detect cross-segments connecting the boundary pixels. A quadrilateral classifier is trained and used to detect quadrilaterals connecting the cross segments. Dynamic programming is then used to combine the quadrilaterals to generate a tubular structure representing the vessel.
摘要翻译：公开了一种用于荧光镜图像中血管分割的方法和系统。使用基于层次学习的检测来执行血管分割。边界分类器被训练并用于检测透视图像中血管的边界像素。训练跨段分类器，用于检测连接边界像素的交叉段。四边形分类器被训练并用于检测连接横截面的四边形。然后使用动态规划来组合四边形以产生代表该容器的管状结构。

88. 发明授权

US08086006B2 Method and system for evaluating image segmentation based on visibility 有权
标题翻译：基于可见度评估图像分割的方法和系统
公开(公告)号：US08086006B2
公开(公告)日：2011-12-27
申请号：US12231634
申请日：2008-09-04
申请人： Wei Zhang , Adrian Barbu , Simone Prummer , Martin Ostermeier , Dorin Comaniciu
发明人： Wei Zhang , Adrian Barbu , Simone Prummer , Martin Ostermeier , Dorin Comaniciu
IPC分类号： G06K9/00
CPC分类号： G06T7/60 , G06T7/11 , G06T7/174 , G06T7/246 , G06T2207/10121 , G06T2207/30048 , G06T2207/30101
摘要： A method and system for evaluating image segmentation is disclosed. In order to quantitatively evaluate an image segmentation technique, synthetic image data is generated and the synthetic image data is segmented to extract an object using the segmentation technique. This segmentation results in a foreground containing the extracted object and a background. The visibility of the extracted object is quantitatively measured based on the intensity distributions of the segmented foreground and background. The visibility is quantitatively measured by calculating the Jeffries-Matusita distance between the foreground and background intensity distributions. This method can be used to evaluate segmentation of vessels in fluoroscopic image sequences by coronary digital subtraction angiography (DSA).
摘要翻译：公开了一种用于评估图像分割的方法和系统。为了定量评估图像分割技术，生成合成图像数据，并且使用分割技术对合成图像数据进行分割以提取对象。该分割导致包含提取的对象和背景的前景。基于分割的前景和背景的强度分布，定量地测量提取的对象的可视性。通过计算前景和背景强度分布之间的Jeffries-Matusita距离来定量测量可见度。该方法可用于通过冠状动脉数字减影血管造影（DSA）评估荧光镜图像序列中血管的分割。

89. 发明授权

US08068654B2 Method and system for detection and registration of 3D objects using incremental parameter learning 有权
标题翻译：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：US08068654B2
公开(公告)日：2011-11-29
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： G06K9/00 , G06T15/00
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，基于从先前的训练步骤得到的检测到的候选，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。

90. 发明授权

US08060178B2 System and method for performing probabilistic classification and decision support using multidimensional medical image databases 有权
标题翻译：使用多维医学图像数据库执行概率分类和决策支持的系统和方法
公开(公告)号：US08060178B2
公开(公告)日：2011-11-15
申请号：US12243199
申请日：2008-10-01
申请人： Xiang Zhou , Dorin Comaniciu , Alok Gupta , Visvanathan Ramesh , Bhavani Duggirala , Diane Paine
发明人： Xiang Zhou , Dorin Comaniciu , Alok Gupta , Visvanathan Ramesh , Bhavani Duggirala , Diane Paine
IPC分类号： A61B5/00
CPC分类号： G06K9/6276 , A61B8/0883 , G06F19/00 , G06K9/6256 , G06K2209/05 , G06Q50/22 , G16H50/20 , Y10S128/92 , Y10S128/924
摘要： A system and method for providing decision support to a physician during a medical examination is disclosed. Data is received from a sensor representing a particular medical measurement. The received data includes image data. The received data and context data is analyzed with respect to one or more sets of training models. Probability values for the particular medical measurement and other measurements to be taken are derived based on the analysis and based on identified classes. The received image data is compared with training images. Distance values are determined between the received image data and the training images, and the training images are associated with the identified classes. Absolute value feature sensitivity scores are derived for the particular medical measurement and other measurements to be taken based on the analysis. The probability values, distance values and absolute value feature sensitivity scores are outputted to the user.
摘要翻译：公开了一种用于在医学检查期间向医师提供决策支持的系统和方法。从代表特定医疗测量的传感器接收数据。所接收的数据包括图像数据。相对于一组或多组训练模型分析接收到的数据和上下文数据。特定医疗测量和其他测量的概率值基于分析并基于识别的类别导出。将接收到的图像数据与训练图像进行比较。在接收的图像数据和训练图像之间确定距离值，并且训练图像与所识别的类别相关联。基于分析，针对特定医疗测量和其他测量得出绝对值特征灵敏度得分。将概率值，距离值和绝对值特征灵敏度得分输出给用户。

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