公开(公告)号：US10719986B2

公开(公告)日：2020-07-21

申请号：US12975714

申请日：2010-12-22

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

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

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

Abstract: 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：US10311978B2

公开(公告)日：2019-06-04

申请号：US13754174

申请日：2013-01-30

Applicant: Tommaso Mansi ,  Bogdan Georgescu ,  Xudong Zheng ,  Ali Kamen ,  Dorin Comaniciu

Inventor： Tommaso Mansi ,  Bogdan Georgescu ,  Xudong Zheng ,  Ali Kamen ,  Dorin Comaniciu

IPC: G06F17/50 ,  A61B5/055 ,  A61N1/362 ,  A61N1/365 ,  G06F19/00 ,  G06T17/00 ,  G09B23/30 ,  G16H50/50 ,  A61B5/00 ,  A61B8/08

CPC classification number: G06F17/5009 ,  A61B5/0044 ,  A61B5/055 ,  A61B8/0883 ,  A61B2576/023 ,  A61N1/3627 ,  A61N1/36514 ,  A61N1/36585 ,  G06T17/00 ,  G06T2210/41 ,  G09B23/30 ,  G16H50/50

Abstract: A method and system for patient-specific planning of cardiac therapy, such as cardiac resynchronization therapy (CRT), based on preoperative clinical data and medical images, such as ECG data, magnetic resonance imaging (MRI) data, and ultrasound data, is disclosed. A patient-specific anatomical model of the left and right ventricles is generated from medical image data of a patient. A patient-specific computational heart model, which comprises cardiac electrophysiology, biomechanics and hemodynamics, is generated based on the patient-specific anatomical model of the left and right ventricles and clinical data. Simulations of cardiac therapies, such as CRT at one or more anatomical locations are performed using the patient-specific computational heart model. Changes in clinical cardiac parameters are then computed from the patient-specific model, constituting predictors of therapy outcome useful for therapy planning and optimization.

公开(公告)号：US09846765B2

公开(公告)日：2017-12-19

申请号：US14071688

申请日：2013-11-05

Applicant: Chloe Audigier ,  Tommaso Mansi ,  Viorel Mihalef ,  Ali Kamen ,  Dorin Comaniciu ,  Puneet Sharma ,  Saikiran Rapaka ,  Herve Delingette ,  Nicholas Ayache

Inventor： Chloe Audigier ,  Tommaso Mansi ,  Viorel Mihalef ,  Ali Kamen ,  Dorin Comaniciu ,  Puneet Sharma ,  Saikiran Rapaka ,  Herve Delingette ,  Nicholas Ayache

IPC: G06F19/00 ,  G06F19/10 ,  G09B23/30

CPC classification number: G16H50/50 ,  G06F19/00 ,  G06F19/3481 ,  G09B23/30

Abstract: A method and system for tumor ablation planning and guidance based on a patient-specific model of liver tumor ablation is disclosed. A patient-specific anatomical model of the liver and circulatory system of the liver is estimated from 3D medical image data of a patient. Blood flow in the liver and the circulatory system of the liver is simulated based on the patient-specific anatomical model. Heat diffusion due to ablation is simulated based on a virtual ablation probe position and the simulated blood flow in the liver and the venous system of the liver. Cellular necrosis in the liver is simulated based on the simulated heat diffusion. A visualization of a simulated necrosis region is generated and displayed to the user for decision making and optimal therapy planning and guidance.

公开(公告)号：US09805473B2

公开(公告)日：2017-10-31

申请号：US12558736

申请日：2009-09-14

Applicant: Michael Wels ,  Gustavo Henrique Monteiro de Barros Carneiro ,  Martin Huber ,  Dorin Comaniciu ,  Yefeng Zheng

Inventor： Michael Wels ,  Gustavo Henrique Monteiro de Barros Carneiro ,  Martin Huber ,  Dorin Comaniciu ,  Yefeng Zheng

IPC: G06T7/143 ,  G06T7/11

CPC classification number: G06T7/143 ,  G06T7/11 ,  G06T2207/10088 ,  G06T2207/30016

Abstract: A method and system for segmenting multiple brain structures in 3D magnetic resonance (MR) images is disclosed. After intensity standardization of a 3D MR image, a meta-structure including center positions of multiple brain structures is detected in the 3D MR image. The brain structures are then individually segmented using marginal space learning (MSL) constrained by the detected meta-structure.

公开(公告)号：US09761004B2

公开(公告)日：2017-09-12

申请号：US12487223

申请日：2009-06-18

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

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

IPC: A61B6/03 ,  G06T7/00 ,  G06T7/13

CPC classification number: G06T7/13 ,  G06T7/0012 ,  G06T2207/10081 ,  G06T2207/20044 ,  G06T2207/20081 ,  G06T2207/30048 ,  G06T2207/30101

Abstract: 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：US09700276B2

公开(公告)日：2017-07-11

申请号：US13780149

申请日：2013-02-28

Applicant: Lei Zhang ,  Wen Wu ,  Terrence Chen ,  Norbert Strobel ,  Dorin Comaniciu

Inventor： Lei Zhang ,  Wen Wu ,  Terrence Chen ,  Norbert Strobel ,  Dorin Comaniciu

IPC: A61B1/04 ,  A61B1/00 ,  A61B6/00 ,  A61B6/12 ,  G06T7/246 ,  A61B90/00 ,  A61B34/20

CPC classification number: A61B6/5211 ,  A61B6/12 ,  A61B6/485 ,  A61B6/487 ,  A61B2034/2065 ,  A61B2090/376 ,  G06T7/248 ,  G06T2207/30021

Abstract: A computer-implemented method for tracking one or more objects in a sequence of images includes generating a dictionary based on object locations in a first image included in the sequence of images. One or more object landmark candidates are identified in the sequence of images and a plurality of tracking hypothesis for the object landmark candidates are generated. A first tracking hypothesis is selected from the plurality of tracking hypothesis based on the dictionary.

公开(公告)号：US09375195B2

公开(公告)日：2016-06-28

申请号：US13905939

申请日：2013-05-30

Applicant: Ali Kamen ,  Tommaso Mansi ,  Bogdan Georgescu ,  Dorin Comaniciu

Inventor： Ali Kamen ,  Tommaso Mansi ,  Bogdan Georgescu ,  Dorin Comaniciu

IPC: G06K9/00 ,  A61B8/08 ,  A61B8/13 ,  A61B10/02 ,  A61B5/00 ,  G06T7/00 ,  A61B5/05 ,  A61B5/055 ,  A61B8/14 ,  A61B8/00

CPC classification number: A61B8/0841 ,  A61B5/055 ,  A61B5/7425 ,  A61B8/13 ,  A61B8/14 ,  A61B8/4254 ,  A61B8/463 ,  A61B8/483 ,  A61B8/485 ,  A61B8/5261 ,  A61B10/0233 ,  A61B10/0241 ,  G06T7/33 ,  G06T2207/10136 ,  G06T2207/30081

Abstract: A method and system for real-time ultrasound guided prostate needle biopsy based on a biomechanical model of the prostate from 3D planning image data, such as magnetic resonance imaging (MRI) data, is disclosed. The prostate is segmented in the 3D ultrasound image. A reference patient-specific biomechanical model of the prostate extracted from planning image data is fused to a boundary of the segmented prostate in the 3D ultrasound image, resulting in a fused 3D biomechanical prostate model. In response to movement of an ultrasound probe to a new location, a current 2D ultrasound image is received. The fused 3D biomechanical prostate model is deformed based on the current 2D ultrasound image to match a current deformation of the prostate due to the movement of the ultrasound probe to the new location.

Abstract translation: 公开了一种基于3D规划图像数据（如磁共振成像（MRI））数据的前列腺生物力学模型的实时超声引导前列腺穿刺活检的方法和系统。 前列腺在3D超声图像中被分割。 从计划图像数据中提取的前列腺特异性参考生物力学模型融合到3D超声图像中分割的前列腺的边界，产生融合的3D生物力学前列腺模型。 响应于超声探头移动到新位置，接收当前的2D超声图像。 融合的3D生物力学前列腺模型基于当前的2D超声图像而变形，以匹配由于超声探头移动到新位置而导致的前列腺的当前变形。

公开(公告)号：US09119540B2

公开(公告)日：2015-09-01

申请号：US13226779

申请日：2011-09-07

Applicant: Puneet Sharma ,  Bogdan Georgescu ,  Viorel Mihalef ,  Terrence Chen ,  Dorin Comaniciu

Inventor： Puneet Sharma ,  Bogdan Georgescu ,  Viorel Mihalef ,  Terrence Chen ,  Dorin Comaniciu

IPC: A61B5/026 ,  G06T7/00 ,  G06F19/00

CPC classification number: A61B5/026 ,  A61B2576/023 ,  G06F19/321 ,  G06F19/3468 ,  G06T7/0016 ,  G06T2207/10081 ,  G06T2207/10096 ,  G06T2207/10116 ,  G06T2207/30048 ,  G06T2207/30104 ,  G16H20/17 ,  G16H30/20 ,  G16H30/40 ,  G16H50/50

Abstract: In order to assess coronary artery disease from medical image data, an anatomical model of a coronary artery is generated from the medical image data. A velocity of blood in the coronary artery is estimated based on a spatio-temporal representation of contrast agent propagation in the medical image data. Blood flow is simulated in the anatomical model of the coronary artery using a computational fluid dynamics (CFD) simulation using the estimated velocity of the blood in the coronary artery as a boundary condition.

Abstract translation: 为了从医学图像数据中评估冠状动脉疾病，从医学图像数据生成冠状动脉的解剖模型。 基于医学图像数据中的造影剂传播的时空表示来估计冠状动脉中的血液速度。 使用计算流体动力学（CFD）模拟，使用冠状动脉中血液的估计速度作为边界条件，在冠状动脉的解剖模型中模拟血流。

公开(公告)号：US09033887B2

公开(公告)日：2015-05-19

申请号：US13905690

申请日：2013-05-30

Applicant: Razvan Ioan Ionasec ,  Dime Vitanovski ,  Yang Wang ,  Bogdan Georgescu ,  Ingmar Voigt ,  Saurabh Datta ,  Dorin Comaniciu

Inventor： Razvan Ioan Ionasec ,  Dime Vitanovski ,  Yang Wang ,  Bogdan Georgescu ,  Ingmar Voigt ,  Saurabh Datta ,  Dorin Comaniciu

IPC: A61B8/06 ,  A61B5/00 ,  A61B8/08 ,  A61B8/00 ,  A61B8/14 ,  A61B5/107

CPC classification number: A61B8/065 ,  A61B5/1075 ,  A61B5/7264 ,  A61B8/085 ,  A61B8/14 ,  A61B8/463 ,  A61B8/466 ,  A61B8/483 ,  A61B8/486 ,  A61B8/488 ,  A61B8/5223

Abstract: A mitral valve is detected in transthoracic echocardiography. The ultrasound transducer is positioned against the chest of the patient rather than being inserted within the patient. While data acquired from such scanning may be noisier or have less resolution, the mitral valve may still be automatically detected. Using both B-mode data representing tissue as well as flow data representing the regurgitant jet, the mitral valve may be detected automatically with a machine-learnt classifier. A series of classifiers may be used, such as determining a position and orientation of a valve region with one classifier, determining a regurgitant orifice with another classifier, and locating mitral valve anatomy with a third classifier. One or more features for some of the classifiers may be calculated based on the orientation of the valve region.

Abstract translation: 经胸超声心动图检测二尖瓣。 超声换能器位于患者胸部的位置，而不是插入患者体内。 虽然从这种扫描获取的数据可能噪声较大或分辨率较低，但仍可能自动检测二尖瓣。 使用表示组织的B模式数据以及表示反流喷射的流动数据，可以用机器学习的分类器自动检测二尖瓣。 可以使用一系列分类器，例如用一个分类器确定瓣膜区域的位置和取向，使用另一分类器确定反流孔，以及用第三分类器定位二尖瓣解剖。 可以基于阀区域的取向来计算一些分类器的一个或多个特征。

公开(公告)号：US09014423B2

公开(公告)日：2015-04-21

申请号：US13412882

申请日：2012-03-06

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

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

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

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

Abstract: 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.

Abstract translation: 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。