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公开(公告)号：US20050001013A1
公开(公告)日：2005-01-06
申请号：US10842802
申请日：2004-05-11
CPC分类号： G06K9/00281
摘要： A system and method for object detection are provided where the system includes a component detection unit for detecting components in an image, a component fusion unit in signal communication with the component detection unit for fusing the components into an object, and a CPU in signal communication with the detection and fusion units for comparing the fused components with a statistical model; and the method includes receiving observation data for a plurality of training images, forming at least one statistical model from the plurality of training images, receiving an input image having a plurality of pixels, detecting a plurality of components in the input image, determining a fusion of the detected components, comparing the fusion with the statistical model, and detecting an object in accordance with the comparison.
摘要翻译： 提供了一种用于对象检测的系统和方法，其中系统包括用于检测图像中的分量的分量检测单元，与分量检测单元进行信号通信的分量融合单元，用于将分量融合到对象中，以及在信号通信中的CPU 用检测和融合单元比较融合成分与统计模型; 并且该方法包括接收多个训练图像的观测数据，从多个训练图像中形成至少一个统计模型，接收具有多个像素的输入图像，检测输入图像中的多个分量，确定融合 的检测组件，将融合与统计模型进行比较，并根据比较来检测对象。
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公开(公告)号：US07602941B2
公开(公告)日：2009-10-13
申请号：US10842802
申请日：2004-05-11
CPC分类号： G06K9/00281
摘要： A system and method for object detection are provided where the system includes a component detection unit for detecting components in an image, a component fusion unit in signal communication with the component detection unit for fusing the components into an object, and a CPU in signal communication with the detection and fusion units for comparing the fused components with a statistical model; and the method includes receiving observation data for a plurality of training images, forming at least one statistical model from the plurality of training images, receiving an input image having a plurality of pixels, detecting a plurality of components in the input image, determining a fusion of the detected components, comparing the fusion with the statistical model, and detecting an object in accordance with the comparison.
摘要翻译： 提供了一种用于对象检测的系统和方法，其中系统包括用于检测图像中的分量的分量检测单元，与分量检测单元进行信号通信的分量融合单元，用于将分量融合到对象中，以及在信号通信中的CPU 用检测和融合单元比较融合成分与统计模型; 并且该方法包括接收多个训练图像的观测数据，从多个训练图像中形成至少一个统计模型，接收具有多个像素的输入图像，检测输入图像中的多个分量，确定融合 的检测组件，将融合与统计模型进行比较，并根据比较来检测对象。
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3.发明授权Real-time obstacle detection with a calibrated camera and known ego-motion 有权使用校准的相机实现障碍物检测和已知的自我运动公开(公告)号：US07446798B2
公开(公告)日：2008-11-04
申请号：US10770044
申请日：2004-02-02
申请人： Dorin Comaniciu , Binglong Xie
发明人： Dorin Comaniciu , Binglong Xie
IPC分类号： H04N7/18
CPC分类号： G06K9/3241 , G06K2209/23 , G06T7/70
摘要： A method and system of real-time obstacle detection from a moving vehicle is provided. The method and system use a calibrated image capturing device. The method and system use a motion estimation technique to pick points with reliable image motion flows, and performs very fast sparse matching between the image motion flows and true motion flows calculated from the ego-motion of the image capturing device. Any mismatch between the image motion flows and the true motion flows are verified over time to achieve robust obstacle detection.
摘要翻译： 提供了一种来自移动车辆的实时障碍物检测方法和系统。 该方法和系统使用校准的图像捕获装置。 该方法和系统使用运动估计技术来拾取具有可靠图像运动流的点，并且在图像运动流和从图像捕获装置的自身运动计算出的真实运动流之间执行非常快的稀疏匹配。 图像运动流和真实运动流之间的任何不匹配都随时间被验证，以实现鲁棒的障碍物检测。
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4.发明授权System and method for detecting an occupant and head pose using stereo detectors 有权使用立体声检测器检测乘员和头部姿势的系统和方法公开(公告)号：US07508979B2
公开(公告)日：2009-03-24
申请号：US10991684
申请日：2004-11-18
申请人： Dorin Comaniciu , Thorsten Köhler , Binglong Xie , Ying Zhu
发明人： Dorin Comaniciu , Thorsten Köhler , Binglong Xie , Ying Zhu
IPC分类号： G06K9/00
CPC分类号： G06K9/00832 , G06K9/00248 , G06K9/00362 , G06T7/74 , G06T2207/10012 , G06T2207/30201 , G06T2207/30248
摘要： A system and method for detecting an occupant and head pose using stereo detectors is disclosed. In the training stage, pairs of images taken simultaneously from a pair of stereo cameras are received and components in each pair of images are identified. Features are associated with each component and a value is associated with each feature. Among them, a subset of features with best discriminative capabilities is selected and forms a strong classifier for a given component in a pair of images. In the detection stage, the strong classifiers are used in the incoming image pairs to detect components. Identified components are used to detect occupants and head pose of the occupants. Stereo detection is combined with stereo matching in a systematic way to improve occupant detection and localization.
摘要翻译： 公开了一种使用立体声检测器检测乘员和头部姿势的系统和方法。 在训练阶段，接收从一对立体相机同时获取的图像对，并且识别每对图像中的成分。 功能与每个组件相关联，并且值与每个功能相关联。 其中，选择具有最佳辨别能力的特征的子集，并为一对图像中的给定分量形成强分类器。 在检测阶段，强分类器用于输入图像对以检测组件。 识别的组件用于检测乘员的乘客和头部姿势。 立体声检测与系统的立体匹配相结合，提高乘员检测和定位。
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5.发明申请System and method for detecting an occupant and head pose using stereo detectors 有权使用立体声检测器检测乘员和头部姿势的系统和方法公开(公告)号：US20070183651A1
公开(公告)日：2007-08-09
申请号：US10991684
申请日：2004-11-18
申请人： Dorin Comaniciu , Thorsten Kohler , Binglong Xie , Ying Zhu
发明人： Dorin Comaniciu , Thorsten Kohler , Binglong Xie , Ying Zhu
CPC分类号： G06K9/00832 , G06K9/00248 , G06K9/00362 , G06T7/74 , G06T2207/10012 , G06T2207/30201 , G06T2207/30248
摘要： A system and method for detecting an occupant and head pose using stereo detectors is disclosed. In the training stage, pairs of images taken simultaneously from a pair of stereo cameras are received and components in each pair of images are identified. Features are associated with each component and a value is associated with each feature. Among them, a subset of features with best discriminative capabilities is selected and forms a strong classifier for a given component in a pair of images. In the detection stage, the strong classifiers are used in the incoming image pairs to detect components. Identified components are used to detect occupants and head pose of the occupants. Stereo detection is combined with stereo matching in a systematic way to improve occupant detection and localization.
摘要翻译： 公开了一种使用立体声检测器检测乘员和头部姿势的系统和方法。 在训练阶段，接收从一对立体相机同时获取的图像对，并且识别每对图像中的成分。 功能与每个组件相关联，并且值与每个功能相关联。 其中，选择具有最佳辨别能力的特征的子集，并为一对图像中的给定分量形成强分类器。 在检测阶段，强分类器用于输入图像对以检测组件。 识别的组件用于检测乘员的乘客和头部姿势。 立体声检测与系统的立体匹配相结合，提高乘员检测和定位。
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公开(公告)号：US11450431B2
公开(公告)日：2022-09-20
申请号：US14442517
申请日：2013-11-15
摘要： A method of identifying an optimum treatment for a patient suffering from coronary artery disease, comprising: (i) providing patient information selected from: (a) status in the patient of one or more coronary disease associated biomarkers; (b) one or more items of medical history information selected from prior condition history, intervention history and medication history; (c) one or more items of diagnostic history, if the patient has a diagnostic history; and (d) one or more items of demographic data; (ii) aggregating the patient information in: (a) a Bayesian network; (b) a machine learning and neural network; (c) a rule-based system; and (d) a regression-based system; (iii) deriving a predicted probabilistic adverse event outcome for each intervention comprising percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by coronary artery bypass grafting; and (iv) determining the intervention having the lowest predicted probabilistic adverse outcome.
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公开(公告)号：US10325686B2
公开(公告)日：2019-06-18
申请号：US13928430
申请日：2013-06-27
申请人： Tommaso Mansi , Wei Keat Lim , Vanessa King , Andreas Kremer , Bogdan Georgescu , Xudong Zheng , Ali Kamen , Andreas Keller , Cord Friedrich Staehler , Emil Wirsz , Dorin Comaniciu
发明人： Tommaso Mansi , Wei Keat Lim , Vanessa King , Andreas Kremer , Bogdan Georgescu , Xudong Zheng , Ali Kamen , Andreas Keller , Cord Friedrich Staehler , Emil Wirsz , Dorin Comaniciu
摘要： A system operating in a plurality of modes to provide an integrated analysis of molecular data, imaging data, and clinical data associated with a patient includes a multi-scale model, a molecular model, and a linking component. The multi-scale model is configured to generate one or more estimated multi-scale parameters based on the clinical data and the imaging data when the system operates in a first mode, and generate a model of organ functionality based on one or more inferred multi-scale parameters when the system operates in a second mode. The molecular model is configured to generate one or more first molecular findings based on a molecular network analysis of the molecular data, wherein the molecular model is constrained by the estimated parameters when the system operates in the first mode. The linking component, which is operably coupled to the multi-scale model and the molecular model, is configured to transfer the estimated multi-scale parameters from the multi-scale model to the molecular model when the system operates in the first mode, and generate, using a machine learning process, the inferred multi-scale parameters based on the molecular findings when the system operates in the second mode.
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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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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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10.发明授权公开(公告)号：US09785858B2
公开(公告)日：2017-10-10
申请号：US12567197
申请日：2009-09-25
申请人： Sascha Seifert , Adrian Barbu , Shaohua Kevin Zhou , David Liu , Johannes Feulner , Martin Huber , Michael Suehling , Alexander Cavallaro , Dorin Comaniciu
发明人： Sascha Seifert , Adrian Barbu , Shaohua Kevin Zhou , David Liu , Johannes Feulner , Martin Huber , Michael Suehling , Alexander Cavallaro , Dorin Comaniciu
CPC分类号： G06K9/4638 , G06K2209/05 , G06T7/11 , G06T7/143 , G06T2207/10081 , G06T2207/20081 , G06T2207/20128 , G06T2207/30048 , G06T2207/30056
摘要： A method and apparatus for hierarchical parsing and semantic navigation of a full or partial body computed tomography CT scan is disclosed. In particular, organs are segmented and anatomic landmarks are detected in a full or partial body CT volume. One or more predetermined slices of the CT volume are detected. A plurality of anatomic landmarks and organ centers are then detected in the CT volume using a discriminative anatomical network, each detected in a portion of the CT volume constrained by at least one of the detected slices. A plurality of organs, such as heart, liver, kidneys, spleen, bladder, and prostate, are detected in a sense of a bounding box and segmented in the CT volume, detection of each organ bounding box constrained by the detected organ centers and anatomic landmarks. Organ segmentation is via a database-guided segmentation method.
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