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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。
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公开(公告)号：US09999399B2
公开(公告)日：2018-06-19
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
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.
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3.发明授权公开(公告)号：US09582934B2
公开(公告)日：2017-02-28
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
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。
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4.发明申请公开(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
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。
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5.发明授权Method and system for catheter tracking in fluoroscopic images using adaptive discriminant learning and measurement fusion 有权使用自适应判别学习和测量融合的荧光镜图像中导管跟踪的方法和系统公开(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
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。
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公开(公告)号：US09824302B2
公开(公告)日：2017-11-21
申请号：US13412869
申请日：2012-03-06
申请人： Sasa Grbic , Razvan Ioan Ionasec , Yang Wang , Bogdan Georgescu , Tommaso Mansi , Dorin Comaniciu , Yefeng Zheng , Shaohua Kevin Zhou , Matthias John , Jan Boese
发明人： Sasa Grbic , Razvan Ioan Ionasec , Yang Wang , Bogdan Georgescu , Tommaso Mansi , Dorin Comaniciu , Yefeng Zheng , Shaohua Kevin Zhou , Matthias John , Jan Boese
CPC分类号： G06K9/6289 , G06K9/6211
摘要： A method and system for fusion of multi-modal volumetric images is disclosed. A first image acquired using a first imaging modality is received. A second image acquired using a second imaging modality is received. A model and of a target anatomical structure and a transformation are jointly estimated from the first and second images. The model represents a model of the target anatomical structure in the first image and the transformation projects a model of the target anatomical structure in the second image to the model in the first image. The first and second images can be fused based on estimated transformation.
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7.发明申请Method and System for Catheter Tracking in Fluoroscopic Images Using Adaptive Discriminant Learning and Measurement Fusion 有权使用自适应判别学习和测量融合的荧光图像中导管跟踪的方法和系统公开(公告)号：US20120238866A1
公开(公告)日：2012-09-20
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
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。
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8.发明申请公开(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。
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9.发明申请公开(公告)号：US20120230568A1
公开(公告)日：2012-09-13
申请号：US13412869
申请日：2012-03-06
申请人： Sasa Grbic , Razvan Ioan Ionasec , Yang Wang , Bogdan Georgescu , Tommaso Mansi , Dorin Comaniciu , Yefeng Zheng , Shaohua Kevin Zhou , Matthias John , Jan Boese
发明人： Sasa Grbic , Razvan Ioan Ionasec , Yang Wang , Bogdan Georgescu , Tommaso Mansi , Dorin Comaniciu , Yefeng Zheng , Shaohua Kevin Zhou , Matthias John , Jan Boese
IPC分类号： G06K9/36
CPC分类号： G06K9/6289 , G06K9/6211
摘要： A method and system for fusion of multi-modal volumetric images is disclosed. A first image acquired using a first imaging modality is received. A second image acquired using a second imaging modality is received. A model and of a target anatomical structure and a transformation are jointly estimated from the first and second images. The model represents a model of the target anatomical structure in the first image and the transformation projects a model of the target anatomical structure in the second image to the model in the first image. The first and second images can be fused based on estimated transformation.
摘要翻译： 公开了一种用于融合多模体积图像的方法和系统。 接收使用第一成像模式获取的第一图像。 接收使用第二成像模态获取的第二图像。 从第一和第二图像共同估计模型和目标解剖结构和变换。 该模型表示第一图像中目标解剖结构的模型，并且变换将第二图像中的目标解剖结构的模型投影到第一图像中的模型。 可以基于估计的变换来融合第一和第二图像。
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公开(公告)号：US09715637B2
公开(公告)日：2017-07-25
申请号：US12725679
申请日：2010-03-17
申请人： Yefeng Zheng , Bogdan Georgescu , Matthias John , Jan Boese , Dorin Comaniciu
发明人： Yefeng Zheng , Bogdan Georgescu , Matthias John , Jan Boese , Dorin Comaniciu
CPC分类号： G06K9/4638 , G06K2209/051 , G06T7/12 , G06T2200/04 , G06T2207/10081 , G06T2207/30101
摘要： A method and system for aorta segmentation in a 3D volume, such as a C-arm CT volume is disclosed. The aortic root is detected in the 3D volume using marginal space learning (MSL) based segmentation. The aortic arch is detected in the 3D volume using MSL based segmentation. The ascending aorta is tracked from the aortic root to the aortic arch in the 3D volume, and the descending aorta is tracked from the aortic arch in the 3D volume.
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