公开(公告)号：US08009900B2

公开(公告)日：2011-08-30

申请号：US11856208

申请日：2007-09-17

申请人： Adrian Barbu ,  Yefeng Zheng ,  Jing Yang ,  Bogdan Georgescu ,  Dorin Comaniciu

发明人： Adrian Barbu ,  Yefeng Zheng ,  Jing Yang ,  Bogdan Georgescu ,  Dorin Comaniciu

IPC分类号： G06K9/00 ,  G06K9/62

CPC分类号： G06K9/6292

摘要： A system and method for detecting an object in a high dimensional image space is disclosed. A three dimensional image of an object is received. A first classifier is trained in the marginal space of the object center location which generates a predetermined number of candidate object center locations. A second classifier is trained to identify potential object center locations and orientations from the predetermined number of candidate object center locations and maintaining a subset of the candidate object center locations. A third classifier is trained to identify potential locations, orientations and scale of the object center from the subset of the candidate object center locations. A single candidate object pose for the object is identified.

摘要翻译： 公开了一种用于检测高维图像空间中的对象的系统和方法。 接收对象的三维图像。 在对象中心位置的边缘空间中训练第一分类器，其生成预定数量的候选对象中心位置。 训练第二分类器以从预定数量的候选对象中心位置识别潜在对象中心位置和方向，并维护候选对象中心位置的子集。 训练第三分类器以从候选对象中心位置的子集中识别对象中心的潜在位置，方向和尺度。 识别对象的单个候选对象姿势。

公开(公告)号：US20110096969A1

公开(公告)日：2011-04-28

申请号：US12877168

申请日：2010-09-08

申请人： Yefeng Zheng ,  Matthias John ,  Jan Boese ,  Dorin Comaniciu

发明人： Yefeng Zheng ,  Matthias John ,  Jan Boese ,  Dorin Comaniciu

IPC分类号： G06K9/00

CPC分类号： G06K9/00214 ,  A61B6/032 ,  A61B6/4441 ,  A61B6/503 ,  A61B6/504 ,  A61B6/5211 ,  G06K9/6209

摘要： A system and method for performing shape-constrained aortic valve landmark detection using 3D medical images is provided. A rigid global shape defining initial positions of a plurality of aortic valve landmarks is detected within a 3D image. Each of the plurality of aortic valve landmarks is detected based on the initial positions.

摘要翻译： 提供了一种用于使用3D医学图像进行形状约束的主动脉瓣地标检测的系统和方法。 在3D图像内检测限定多个主动脉瓣地标的初始位置的刚性全局形状。 基于初始位置检测多个主动脉瓣标记中的每一个。

公开(公告)号：US20110096964A1

公开(公告)日：2011-04-28

申请号：US12901600

申请日：2010-10-11

申请人： Yefeng Zheng ,  David Liu ,  Jan Boese ,  Dorin Comaniciu

发明人： Yefeng Zheng ,  David Liu ,  Jan Boese ,  Dorin Comaniciu

IPC分类号： G06K9/00

CPC分类号： G06T7/77 ,  G06T7/12 ,  G06T7/143 ,  G06T7/149 ,  G06T2207/10072 ,  G06T2207/20081 ,  G06T2207/20124 ,  G06T2207/30048

摘要： A method and system for automatic extraction of personalized left atrium models is disclosed. A left atrium chamber body is segmented from a 3D image volume. At least one pulmonary venous ostium is detected on the segmented left atrium chamber body. At least one pulmonary vein trunk connected to the left atrium chamber body is segmented based on the detected pulmonary venous ostia.

摘要翻译： 公开了一种用于自动提取个性化左心房模型的方法和系统。 左心房腔体从3D图像体积分割。 在分割的左心房腔体上检测到至少一个肺静脉口。 基于检测到的肺静脉口，将连接到左心房腔体的至少一个肺静脉干线分段。

公开(公告)号：US10719986B2

公开(公告)日：2020-07-21

申请号：US12975714

申请日：2010-12-22

申请人： Dominik Zaeuner ,  Razvan Ioan Ionasec ,  Bogdan Georgescu ,  Yefeng Zheng ,  Dorin Comaniciu ,  Ingmar Voigt ,  Jan Boese

发明人： Dominik Zaeuner ,  Razvan Ioan Ionasec ,  Bogdan Georgescu ,  Yefeng Zheng ,  Dorin Comaniciu ,  Ingmar Voigt ,  Jan Boese

IPC分类号： G06T17/00 ,  G06T19/00 ,  G16H50/50 ,  G06F19/00

摘要： A method and system for virtual percutaneous valve implantation is disclosed. A patient-specific anatomical model of a heart valve is estimated based on 3D cardiac medical image data and an implant model representing a valve implant is virtually deployed into the patient-specific anatomical model of the heart valve. A library of implant models, each modeling geometrical properties of a corresponding valve implant, is maintained. The implant models maintained in the library are virtually deployed into the patient specific anatomical model of the heart valve to select an implant type and size and deployment location and orientation for percutaneous valve implantation.

公开(公告)号：US09761004B2

公开(公告)日：2017-09-12

申请号：US12487223

申请日：2009-06-18

申请人： Sushil Mittal ,  Yefeng Zheng ,  Bogdan Georgescu ,  Fernando Vega-Higuera ,  Dorin Comaniciu

发明人： Sushil Mittal ,  Yefeng Zheng ,  Bogdan Georgescu ,  Fernando Vega-Higuera ,  Dorin Comaniciu

IPC分类号： A61B6/03 ,  G06T7/00 ,  G06T7/13

CPC分类号： G06T7/13 ,  G06T7/0012 ,  G06T2207/10081 ,  G06T2207/20044 ,  G06T2207/20081 ,  G06T2207/30048 ,  G06T2207/30101

摘要： A method and system for automatic coronary stenosis detection in computed tomography (CT) data is disclosed. Coronary artery centerlines are obtained in an input cardiac CT volume. A trained classifier, such as a probabilistic boosting tree (PBT) classifier, is used to detect stenosis regions along the centerlines in the input cardiac CT volume. The classifier classifies each of the control points that define the coronary artery centerlines as a stenosis point or a non-stenosis point.

公开(公告)号：US09014423B2

公开(公告)日：2015-04-21

申请号：US13412882

申请日：2012-03-06

申请人： Peng Wang ,  Yefeng Zheng ,  Matthias John ,  Jan Boese ,  Gareth Funka-Lea ,  Dorin Comaniciu

发明人： Peng Wang ,  Yefeng Zheng ,  Matthias John ,  Jan Boese ,  Gareth Funka-Lea ,  Dorin Comaniciu

IPC分类号： G06K9/00 ,  A61B6/00 ,  A61B6/12 ,  G06T7/20

CPC分类号： A61B6/487 ,  A61B6/12 ,  A61B6/503 ,  G06T7/246 ,  G06T2207/10016 ,  G06T2207/10064 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/30021 ,  G06T2207/30048

摘要： A method and system for adaptive discriminant learning and measurement fusion for image based catheter tracking is disclosed. An adaptive discriminant model is trained online based on a tracked object, such as a pigtail catheter tip, in at least one previous frame of a fluoroscopic image sequence. The object is tracked in the current frame of the fluoroscopic image sequence based at least on the adaptive discriminant model trained online. The object may be tracked in the current frame based on a fusion of three types of measurement models including the adaptive discriminant model trained online, an object detection model trained offline, and an online appearance model.

摘要翻译： 公开了一种用于基于图像的导管跟踪的自适应判别学习和测量融合的方法和系统。 在荧光镜像图像序列的至少一个先前帧中，基于跟踪对象（例如尾纤导管尖端）在线训练自适应判别模型。 至少基于在线训练的自适应判别模型，在透视图像序列的当前帧中跟踪对象。 基于三种类型的测量模型的融合，可以在当前帧中跟踪对象，包括在线训练的自适应判别模型，离线训练的对象检测模型和在线外观模型。

公开(公告)号：US08744172B2

公开(公告)日：2014-06-03

申请号：US13160744

申请日：2011-06-15

申请人： Alexey Tsymbal ,  Michael Kelm ,  Maria Jimena Costa ,  Shaohua Kevin Zhou ,  Dorin Comaniciu ,  Yefeng Zheng ,  Alexander Schwing

发明人： Alexey Tsymbal ,  Michael Kelm ,  Maria Jimena Costa ,  Shaohua Kevin Zhou ,  Dorin Comaniciu ,  Yefeng Zheng ,  Alexander Schwing

IPC分类号： G06K9/00

CPC分类号： G06K9/6219 ,  G06F17/30247 ,  G06F17/30268 ,  G06K9/6263 ,  G06K9/6282

摘要： A method of performing image retrieval includes training a random forest RF classifier based on low-level features of training images and a high-level feature, using similarity values generated by the RF classifier to determine a subset of the training images that are most similar to one another, and classifying input images for the high-level feature using the RF classifier and the determined subset of images.

摘要翻译： 执行图像检索的方法包括基于训练图像的低级特征和高级特征来训练随机森林RF分类器，使用由RF分类器生成的相似性值来确定最相似的训练图像的子集 并且使用RF分类器和确定的图像子集对高级特征的输入图像进行分类。

公开(公告)号：US08682626B2

公开(公告)日：2014-03-25

申请号：US13091076

申请日：2011-04-20

申请人： Razvan Ioan Ionasec ,  Ingmar Voigt ,  Viorel Mihalef ,  Sasa Grbic ,  Dime Vitanovski ,  Yang Wang ,  Yefeng Zheng ,  Bogdan Georgescu ,  Dorin Comaniciu ,  Puneet Sharma ,  Tommaso Mansi

发明人： Razvan Ioan Ionasec ,  Ingmar Voigt ,  Viorel Mihalef ,  Sasa Grbic ,  Dime Vitanovski ,  Yang Wang ,  Yefeng Zheng ,  Bogdan Georgescu ,  Dorin Comaniciu ,  Puneet Sharma ,  Tommaso Mansi

IPC分类号： G06G7/48

CPC分类号： G06T13/20 ,  G06F19/321 ,  G06T2210/24 ,  G06T2210/41 ,  G16H50/50

摘要： A method and system for patient-specific modeling of the whole heart anatomy, dynamics, hemodynamics, and fluid structure interaction from 4D medical image data is disclosed. The anatomy and dynamics of the heart are determined by estimating patient-specific parameters of a physiological model of the heart from the 4D medical image data for a patient. The patient-specific anatomy and dynamics are used as input to a 3D Navier-Stokes solver that derives realistic hemodynamics, constrained by the local anatomy, along the entire heart cycle. Fluid structure interactions are determined iteratively over the heart cycle by simulating the blood flow at a given time step and calculating the deformation of the heart structure based on the simulated blood flow, such that the deformation of the heart structure is used in the simulation of the blood flow at the next time step. The comprehensive patient-specific model of the heart representing anatomy, dynamics, hemodynamics, and fluid structure interaction can be used for non-invasive assessment and diagnosis of the heart, as well as virtual therapy planning and cardiovascular disease management. Parameters of the comprehensive patient-specific model are changed or perturbed to simulate various conditions or treatment options, and then the patient specific model is recalculated to predict the effect of the conditions or treatment options.

摘要翻译： 公开了一种用于针对4D医学图像数据的整个心脏解剖结构，动力学，血流动力学和流体结构相互作用的患者特异性建模的方法和系统。 通过从患者的4D医学图像数据估计心脏的生理模型的患者特异性参数来确定心脏的解剖学和动力学。 患者特异性解剖学和动力学被用作3D Navier-Stokes求解器的输入，该解算器在整个心脏周期中导出由局部解剖结构约束的现实血液动力学。 流体结构相互作用是通过在给定的时间步长模拟血液流动而在心脏周期上迭代地确定的，并且基于模拟的血液流量计算心脏结构的变形，使得心脏结构的变形用于模拟 血液流动在下一个时间步。 代表解剖学，动力学，血液动力学和流体结构相互作用的心脏综合患者特异性模型可用于心脏的非侵入性评估和诊断，以及虚拟治疗计划和心血管疾病管理。 全面的患者特异性模型的参数被改变或扰动以模拟各种条件或治疗选择，然后重新计算患者特异性模型以预测条件或治疗选择的影响。

公开(公告)号：US08526699B2

公开(公告)日：2013-09-03

申请号：US13040716

申请日：2011-03-04

申请人： Sushil Mittal ,  Yefeng Zheng ,  Bogdan Georgescu ,  Fernando Vega-Higuera ,  Shaohua Kevin Zhou ,  Dorin Comaniciu ,  Michael Kelm ,  Alexey Tsymbal ,  Dominik Bernhardt

发明人： Sushil Mittal ,  Yefeng Zheng ,  Bogdan Georgescu ,  Fernando Vega-Higuera ,  Shaohua Kevin Zhou ,  Dorin Comaniciu ,  Michael Kelm ,  Alexey Tsymbal ,  Dominik Bernhardt

IPC分类号： G06K9/00 ,  A61B5/05 ,  A61B5/02 ,  A61F2/06

CPC分类号： G06T7/0016 ,  G06T7/143 ,  G06T2207/10081 ,  G06T2207/20081 ,  G06T2207/30101 ,  G06T2207/30172

摘要： A method and system for providing detecting and classifying coronary stenoses in 3D CT image data is disclosed. Centerlines of coronary vessels are extracted from the CT image data. Non-vessel regions are detected and removed from the coronary vessel centerlines. The cross-section area of the lumen is estimated based on the coronary vessel centerlines using a trained regression function. Stenosis candidates are detected in the coronary vessels based on the estimated lumen cross-section area, and the significant stenosis candidates are automatically classified as calcified, non-calcified, or mixed.

摘要翻译： 公开了一种在3D CT图像数据中提供冠状动脉狭窄检测和分类的方法和系统。 从CT图像数据中提取冠脉血管的中心线。 从血管中心线检测和移除非血管区域。 使用经过训练的回归函数，基于冠状血管中心线估计管腔的横截面面积。 基于估计的管腔横截面积在冠状血管中检测狭窄候选物，并且显着狭窄候选物被自动分类为钙化，非钙化或混合。

公开(公告)号：US20120123250A1

公开(公告)日：2012-05-17

申请号：US13297373

申请日：2011-11-16

申请人： Yu Pang ,  Yefeng Zheng ,  Matthias John ,  Jan Boese ,  Dorin Comaniciu

发明人： Yu Pang ,  Yefeng Zheng ,  Matthias John ,  Jan Boese ,  Dorin Comaniciu

IPC分类号： A61B6/00

CPC分类号： A61B6/487 ,  A61B6/12 ,  A61B6/5264 ,  G06T7/246 ,  G06T7/277 ,  G06T2207/10121 ,  G06T2207/30021

摘要： A method and system for autoregressive model based pigtail catheter motion prediction in a fluoroscopic image sequence is disclosed. Parameters of an autoregressive model are estimated based on observed pigtail catheter tip positions in a plurality of previous frames of a fluoroscopic image sequence. A pigtail catheter tip position in a current frame of the fluoroscopic image sequence is predicted using the fitted autoregressive model. The predicted pigtail catheter tip position can be used to constrain pigtail catheter tip detection in the current frame. The predicted pigtail catheter tip position may also be used to predict abnormal motion in the fluoroscopic image sequence.

摘要翻译： 公开了一种在透视图像序列中基于自回归模型的尾纤导管运动预测的方法和系统。 基于在透视图像序列的多个先前帧中的观察到的尾纤导管尖端位置来估计自回归模型的参数。 使用拟合的自回归模型预测荧光镜图像序列的当前帧中的尾纤导管尖端位置。 预测的猪尾导管尖端位置可用于限制当前帧中的尾纤导管尖端检测。 预测的猪尾导管尖端位置也可以用于预测荧光镜像图像序列中的异常运动。