公开(公告)号：US07940971B2

公开(公告)日：2011-05-10

申请号：US11779405

申请日：2007-07-18

申请人： Wei Zhang ,  Adrian Barbu ,  Simone Prummer ,  Martin Ostermeier ,  Chandan K. Reddy ,  Dorin Comaniciu

发明人： Wei Zhang ,  Adrian Barbu ,  Simone Prummer ,  Martin Ostermeier ,  Chandan K. Reddy ,  Dorin Comaniciu

IPC分类号： G06K9/00

CPC分类号： G06K9/34 ,  G06K2209/05 ,  Y10S128/922

摘要： A method and system for extracting motion-based layers from fluoroscopic image sequences are disclosed. Portions of multiple objects, such as anatomical structures, are detected in the fluoroscopic images. Motion of the objects is estimated between the images is the sequence of fluoroscopic images. The images in the fluoroscopic image sequence are then divided into layers based on the estimated motion. In a particular implementation, the coronary vessel tree and the diaphragm can be extracted in separate motion layers from coronary angiograph fluoroscopic image sequence.

摘要翻译： 公开了一种从透视图像序列中提取基于运动的层的方法和系统。 在透视图像中检测到多个对象的部分，例如解剖结构。 在图像之间估计物体的运动是荧光图像的序列。 然后，基于估计的运动将透视图像序列中的图像分成多个层。 在特定的实施方案中，冠状动脉血管和隔膜可以与冠状动脉血管造影术透视图像序列分开提取。

公开(公告)号：US20090080729A1

公开(公告)日：2009-03-26

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： A61B5/00

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。

公开(公告)号：US20090062641A1

公开(公告)日：2009-03-05

申请号：US12221732

申请日：2008-08-06

申请人： Adrian Barbu ,  Wei Zhang ,  Norbert Strobel ,  Adam K. Galant ,  Ulrich Bill ,  Dorin Comaniciu

发明人： Adrian Barbu ,  Wei Zhang ,  Norbert Strobel ,  Adam K. Galant ,  Ulrich Bill ,  Dorin Comaniciu

IPC分类号： A61B5/05

CPC分类号： A61B34/20 ,  A61B2090/376

摘要： A method and system for detecting and tracking an ablation catheter tip in a fluoroscopic image sequence is disclosed. Catheter tip candidates are detected in each frame of the fluoroscopic image sequence using marginal space learning. The detected catheter tip candidates are then tracked over all the frames of the fluoroscopic image sequence in order to determine an ablation catheter tip location in each frame.

摘要翻译： 公开了一种用于在透视图像序列中检测和跟踪消融导管尖端的方法和系统。 使用边缘空间学习在荧光镜像图像序列的每个帧中检测导管尖端候选。 然后在荧光镜像图像序列的所有帧上跟踪检测到的导管尖端候选，以便确定每个帧中的消融导管尖端位置。

公开(公告)号：US08094903B2

公开(公告)日：2012-01-10

申请号：US12157837

申请日：2008-06-13

申请人： Ying Zhu ,  Wei Zhang ,  Adrian Barbu ,  Simone Prummer ,  Martin Ostermeier ,  Dorin Comaniciu

发明人： Ying Zhu ,  Wei Zhang ,  Adrian Barbu ,  Simone Prummer ,  Martin Ostermeier ,  Dorin Comaniciu

IPC分类号： G06K9/03

CPC分类号： A61B6/504 ,  A61B6/481 ,  G06T5/50 ,  G06T7/215 ,  G06T7/30 ,  G06T2207/10016 ,  G06T2207/10121 ,  G06T2207/30048 ,  G06T2207/30101

摘要： A method and system for extracting coronary vessels fluoroscopic image sequences using coronary digital subtraction angiography (DSA) are disclosed. A set of mask images of a coronary region is received, and a sequence of contrast images for the coronary region is received. For each contrast image, vessel regions are detected in the contrast image using learning-based vessel segment detection and a background region of the contrast image is determined based on the detected vessel regions. Background motion is estimated between one of the mask images and the background region of the contrast image, and the mask image is warped based on the estimated background motion to generate an estimated background layer. The estimated background layer is subtracted from the contrast image to extract a coronary vessel layer for the contrast image.

摘要翻译： 公开了使用冠状动脉数字减影血管造影（DSA）提取冠脉血管荧光镜图像序列的方法和系统。 接收冠状动脉区域的一组掩模图像，并且接收冠状动脉区域的对比度图像序列。 对于每个对比图像，使用基于学习的血管段检测在对比图像中检测血管区域，并且基于检测到的血管区域确定造影剂图像的背景区域。 在掩模图像之一和对比度图像的背景区域之间估计背景运动，并且基于所估计的背景运动来对掩模图像进行翘曲以生成估计的背景层。 从对比图像中减去估计的背景层，以提取对比度图像的冠状血管层。

公开(公告)号：US20090010512A1

公开(公告)日：2009-01-08

申请号：US12157837

申请日：2008-06-13

申请人： Ying Zhu ,  Wei Zhang ,  Adrian Barbu ,  Simone Prummer ,  Martin Ostermeier ,  Dorin Comaniciu

发明人： Ying Zhu ,  Wei Zhang ,  Adrian Barbu ,  Simone Prummer ,  Martin Ostermeier ,  Dorin Comaniciu

IPC分类号： H05G1/64 ,  G06K9/00

CPC分类号： A61B6/504 ,  A61B6/481 ,  G06T5/50 ,  G06T7/215 ,  G06T7/30 ,  G06T2207/10016 ,  G06T2207/10121 ,  G06T2207/30048 ,  G06T2207/30101

摘要： A method and system for extracting coronary vessels fluoroscopic image sequences using coronary digital subtraction angiography (DSA) are disclosed. A set of mask images of a coronary region is received, and a sequence of contrast images for the coronary region is received. For each contrast image, vessel regions are detected in the contrast image using learning-based vessel segment detection and a background region of the contrast image is determined based on the detected vessel regions. Background motion is estimated between one of the mask images and the background region of the contrast image, and the mask image is warped based on the estimated background motion to generate an estimated background layer. The estimated background layer is subtracted from the contrast image to extract a coronary vessel layer for the contrast image.

摘要翻译： 公开了使用冠状动脉数字减影血管造影（DSA）提取冠脉血管荧光镜图像序列的方法和系统。 接收冠状动脉区域的一组掩模图像，并且接收冠状动脉区域的对比度图像序列。 对于每个对比图像，使用基于学习的血管段检测在对比图像中检测血管区域，并且基于检测到的血管区域确定造影剂图像的背景区域。 在掩模图像之一和对比度图像的背景区域之间估计背景运动，并且基于所估计的背景运动来对掩模图像进行翘曲以生成估计的背景层。 从对比图像中减去估计的背景层，以提取对比度图像的冠状血管层。

公开(公告)号：US20080071711A1

公开(公告)日：2008-03-20

申请号：US11856109

申请日：2007-09-17

申请人： Wei Zhang ,  Adrian Barbu ,  Yefeng Zheng ,  Dorin Comaniciu

发明人： Wei Zhang ,  Adrian Barbu ,  Yefeng Zheng ,  Dorin Comaniciu

IPC分类号： G06F15/18

CPC分类号： G06N7/005 ,  G06K9/6257 ,  G06K2209/053

摘要： A method and system for object detection using a probabilistic boosting cascade tree (PBCT) is disclosed. A PBCT is a machine learning based classifier having a structure that is driven by training data and determined during the training process without user input. In a PBCT training method, for each node in the PBCT, a classifier is trained for the node based on training data received at the node. The performance of the classifier trained for the node is then evaluated based on the training data. Based on the performance of the classifier, the node is set to either a cascade node or a tree node. If the performance indicates that the data is relatively easy to classify, the node can be set as a cascade node. If the performance indicates that the data is relatively difficult to classify, the node can be set as a tree node. The trained PBCT can then be used to detect objects or classify data. For example, a trained PBCT can be used to detect lymph nodes in CT volume data.

摘要翻译： 公开了一种使用概率升压级联树（PBCT）进行物体检测的方法和系统。 PBCT是基于机器学习的分类器，其具有由训练数据驱动的结构，并且在训练过程中确定而不需要用户输入。 在PBCT训练方法中，对于PBCT中的每个节点，基于在节点处接收到的训练数据，为节点训练分类器。 然后根据训练数据对针对节点训练的分类器的性能进行评估。 基于分类器的性能，将节点设置为级联节点或树节点。 如果性能指示数据相对容易分类，则可以将节点设置为级联节点。 如果性能指示数据相对较难分类，则可以将节点设置为树节点。 然后，训练有素的PBCT可用于检测对象或对数据进行分类。 例如，训练有素的PBCT可用于检测CT体积数据中的淋巴结。

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。

公开(公告)号：US07558413B2

公开(公告)日：2009-07-07

申请号：US11244798

申请日：2005-10-06

申请人： Zhuowen Tu ,  Xiang Zhou ,  Adrian Barbu ,  Luca Bogoni ,  Dorin Comaniciu

发明人： Zhuowen Tu ,  Xiang Zhou ,  Adrian Barbu ,  Luca Bogoni ,  Dorin Comaniciu

IPC分类号： G06K9/00

CPC分类号： G06K9/4614 ,  G06K9/6206 ,  G06K9/6214 ,  G06K9/6257 ,  G06K2209/053 ,  G06T7/0012 ,  G06T2207/10072 ,  G06T2207/30032

摘要： A method for detecting target objects in a three dimensional (3D) image volume of an anatomical structure is disclosed. A set of candidate locations in the image volume are obtained. For each candidate location, sub-volumes of at least two different scales are cropped out. Each sub-volume comprises a plurality of voxels. For each of the sub-volumes, each sub-volume is rotated in at least two different orientations. A shape classifier is applied to each sub-volume. If the voxels in the sub-volume pass the shape classifier, a gradient direction is computed for the voxels. If the gradient direction for the voxels is one of a predefined orientation, a probability classifier is applied to the voxels. A probability measure computed by the probability classifier as a confidence measure is used for the sub-volume. If the confidence measure is above a predetermined threshold value, the sub-volume is determined to contain the target object.

摘要翻译： 公开了一种用于检测解剖结构的三维（3D）图像体积中的目标对象的方法。 获得图像体积中的一组候选位置。 对于每个候选位置，剪切出至少两个不同尺度的子体积。 每个子体积包括多个体素。 对于每个子卷，每个子卷以至少两个不同的方向旋转。 形状分类器应用于每个子卷。 如果子体积中的体素通过形状分类器，则为体素计算梯度方向。 如果体素的梯度方向是预定义方向之一，则将概率分类器应用于体元。 将概率分类器计算出的概率度量作为置信度量度用于子卷。 如果置信度高于预定阈值，则确定子卷包含目标对象。

公开(公告)号：US20090074272A1

公开(公告)日：2009-03-19

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： G06K9/00

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。

公开(公告)号：US07783097B2

公开(公告)日：2010-08-24

申请号：US11733287

申请日：2007-04-10

申请人： Adrian Barbu ,  Luca Bogoni ,  Dorin Comaniciu

发明人： Adrian Barbu ,  Luca Bogoni ,  Dorin Comaniciu

IPC分类号： G06K9/00 ,  G06K9/32

CPC分类号： G06K9/6256 ,  G06K9/6282 ,  G06K2209/051

摘要： The present invention is directed to a system and method for populating a database with a set of image sequences of an object. The database is used to detect a tubular structure in the object. A set of images of objects are received in which each image is annotated to show a tubular structure. For each given image, a Probabilistic Boosting Tree (PBT) is used to detect three dimensional (3D) circles. Short tubes are constructed from pairs of approximately aligned 3D circles. A discriminative joint shape and appearance model is used to classify each short tube. A long flexible tube is formed by connecting all of the short tubes. A tubular structure model that comprises a start point, end point and the long flexible tube is identified. The tubular structure model is stored in the database.

摘要翻译： 本发明涉及一种用于用对象的一组图像序列填充数据库的系统和方法。 数据库用于检测对象中的管状结构。 接收一组对象的图像，其中每个图像被注释以显示管状结构。 对于每个给定的图像，使用概率增强树（PBT）来检测三维（3D）圆。 短管由大约对齐的三维圆对构成。 使用歧视关节形状和外观模型对每根短管进行分类。 通过连接所有短管形成长的柔性管。 识别包括起点，终点和长柔性管的管状结构模型。 管状结构模型存储在数据库中。