| Patent application number | Description | Published |
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| 20080240532 | System and Method for Detection of Fetal Anatomies From Ultrasound Images Using a Constrained Probabilistic Boosting Tree - A method for detecting fetal anatomic features in ultrasound images includes providing an ultrasound image of a fetus, specifying an anatomic feature to be detected in a region S determined by parameter vector θ, providing a sequence of probabilistic boosting tree classifiers, each with a pre-specified height and number of nodes. Each classifier computes a posterior probability P(y|S) where yε{−1,+1}, with P(y=+1|S) representing a probability that region S contains the feature, and P(y=−1|S) representing a probability that region S contains background information. The feature is detected by uniformly sampling a parameter space of parameter vector θ using a first classifier with a sampling interval vector used for training said first classifier, and having each subsequent classifier classify positive samples identified by a preceding classifier using a smaller sampling interval vector used for training said preceding classifier. Each classifier forms a union of its positive samples with those of the preceding classifier. | 10-02-2008 |
| 20080262814 | Method and system for generating a four-chamber heart model - A method and system for building a statistical four-chamber heart model from 3D volumes is disclosed. In order to generate the four-chamber heart model, each chamber is modeled using an open mesh, with holes at the valves. Based on the image data in one or more 3D volumes, meshes are generated and edited for the left ventricle (LV), left atrium (LA), right ventricle (RV), and right atrium (RA). Resampling to enforce point correspondence is performed during mesh editing. Important anatomic landmarks in the heart are explicitly represented in the four-chamber heart model of the present invention. | 10-23-2008 |
| 20090074280 | Automated Detection of Planes From Three-Dimensional Echocardiographic Data - A plane position for a standard view is detected from three-dimensional echocardiographic data. The position of the plane within the volume is defined by translation, orientation (rotation), and/or scale. Possible positions are detected and other possible positions are ruled out. The classification of the possible positions occurs sequentially by translation, then orientation, and then scale. The sequential process may limit calculations required to identify the plane position for a desired view. | 03-19-2009 |
| 20090080728 | Method and system for vessel segmentation in fluoroscopic images - A method and system for vessel segmentation in fluoroscopic images is disclosed. Hierarchical learning-based detection is used to perform the vessel segmentation. A boundary classifier is trained and used to detect boundary pixels of a vessel in a fluoroscopic image. A cross-segment classifier is trained and used to detect cross-segments connecting the boundary pixels. A quadrilateral classifier is trained and used to detect quadrilaterals connecting the cross segments. Dynamic programming is then used to combine the quadrilaterals to generate a tubular structure representing the vessel. | 03-26-2009 |
| 20090080745 | Method and system for measuring left ventricle volume - A method and system for measuring the volume of the left ventricle (LV) in a 3D medical image, such as a CT, volume is disclosed. Heart chambers are segmented in the CT volume, including at least the LV endocardium and the LV epicardium. An optimal threshold value is automatically determined based on voxel intensities within the LV endocardium and voxel intensities between the LV endocardium and the LV epicardium. Voxels within the LV endocardium are labeled as blood pool voxels or papillary muscle voxels based on the optimal threshold value. The LV volume can be measured excluding the papillary muscles based on the number of blood pool voxels, and the LV volume can be measured including the papillary muscles based on the total number of voxels within the LV endocardium. | 03-26-2009 |
| 20090090873 | Method and system for detection of contrast injection in fluoroscopic image sequences - A method and system for detecting a spatial and temporal location of a contrast injection in a fluoroscopic image sequence is disclosed. Training volumes generated by stacking a sequence of 2D fluoroscopic images in time order are annotated with ground truth contrast injection points. A heart rate is globally estimated for each training volume, and local frequency and phase is estimated in a neighborhood of the ground truth contrast injection point for each training volume. Frequency and phase invariant features are extracted from each training volume based on the heart rate, local frequency and phase, and a detector is trained based on the training volumes and the features extracted for each training volume. The detector can be used to detect the spatial and temporal location of a contrast injection in a fluoroscopic image sequence. | 04-09-2009 |
| 20090093717 | Automated Fetal Measurement From Three-Dimensional Ultrasound Data - A fetal parameter or anatomy is measured or detected from three-dimensional ultrasound data. An algorithm is machine-trained to detect fetal anatomy. Any machine training approach may be used. The machine-trained classifier is a joint classifier, such that one anatomy is detected using the ultrasound data and the detected location of another anatomy. The machine-trained classifier uses marginal space such that the location of anatomy is detected sequentially through translation, orientation and scale rather than detecting for all location parameters at once. The machine-trained classifier includes detectors for detecting from the ultrasound data at different resolutions, such as in a pyramid volume. | 04-09-2009 |
| 20090123050 | Method and system for automatic quantification of aortic valve function from 4D computed tomography data using a physiological model - A method and system for modeling the aortic valve in 4D image data, such as 4D CT and echocardiography, is disclosed. An initial estimate of a physiological aortic valve model is determined for at least one reference frame of a 4D image sequence based on anatomic features in the reference frame. The initial estimate is refined to generate a final estimate in the reference frame. A dynamic model of the aortic valve is then generated by estimating the physiological aortic valve model for each remaining frame of the 4D image sequence based on the final estimate in the reference frame. The aortic valve can be quantitatively evaluated using the dynamic model. | 05-14-2009 |
| 20090124886 | Method For Developing Test For Neurosychiatric Disease - A method for generating classifiers for identifying neuropsychiatric disease includes acquiring functional neuroimaging data. The acquired functional neuroimaging data may be registered to an atlas of the brain. A discriminative mask is generated based on the registered functional neuroimaging data and the generated discriminative mask is applied to the registered functional neuroimaging data. One or more classifiers are generated for identifying neuropsychiatric disease based on the masked functional neuroimaging data. The accuracy of the generated classifiers may be verified. The generated classifiers may then be used to identify neuropsychiatric disease. | 05-14-2009 |
| 20090154785 | Method and system for dynamic pulmonary trunk modeling in computed tomography and magnetic resonance imaging - A method and system for modeling the pulmonary trunk in 4D image data, such as 4D CT and MRI data, is disclosed. Bounding boxes are detected in frames of the 4D image data. Anatomic landmarks are detected in the frames of the 4D image data based on the bounding boxes. Ribs or centerlines of the pulmonary artery are detected in the frames of the 4D image data based on the anatomic landmarks, and a physiological pulmonary trunk model is fit the frames of the 4D image data based on the detected ribs and anatomic landmarks. The boundary of the pulmonary trunk is detected in order to refine the boundary of the pulmonary trunk model in the frames of the 4D image data, resulting in a dynamic model of the pulmonary trunk. The pulmonary trunk can be quantitatively evaluated using the dynamic model. | 06-18-2009 |
| 20090190811 | Method and system for left ventricle endocardium surface segmentation using constrained optimal mesh smoothing - A method and system for left ventricle (LV) endocardium surface segmentation using constrained optimal mesh smoothing is disclosed. The LV endocardium surface in the 3D cardiac volume is initially segmented in a 3D cardiac volume, such as a CT volume, resulting in an LV endocardium surface mesh. A smoothed LV endocardium surface mesh is generated by smoothing the LV endocardium surface mesh using constrained optimal mesh smoothing. The constrained optimal mesh smoothing determines an optimal adjustment for each point on the LV endocardium surface mesh by minimizing an objective function based at least on a smoothness measure, subject to a constraint bounding the adjustment for each point. The adjustment for each point can be constrained to prevent adjustments inward toward the blood pool in order to ensure that the smoothed LV endocardium surface mesh encloses the entire blood pool. | 07-30-2009 |
| 20090304251 | Method and System for Detecting 3D Anatomical Structures Using Constrained Marginal Space Learning - A method and apparatus for detecting 3D anatomical objects in medical images using constrained marginal space learning (MSL) is disclosed. A constrained search range is determined for an input medical image volume based on training data. A first trained classifier is used to detect position candidates in the constrained search range. Position-orientation hypotheses are generated from the position candidates using orientation examples in the training data. A second trained classifier is used to detect position-orientation candidates from the position-orientation hypotheses. Similarity transformation hypotheses are generated from the position-orientation candidates based on scale examples in the training data. A third trained classifier is used to detect similarity transformation candidates from the similarity transformation hypotheses, and the similarity transformation candidates define the position, translation, and scale of the 3D anatomic object in the medical image volume. | 12-10-2009 |
| 20100040272 | Method and System for Left Ventricle Detection in 2D Magnetic Resonance Images - A method and system for left ventricle (LV) detection in 2D magnetic resonance imaging (MRI) images is disclosed. In order to detect the LV in a 2D MRI image, a plurality of LV candidates are detected, for example using marginal space learning (MSL) based detection. Candidates for distinctive anatomic landmarks associated with the LV are then detected in the 2D MRI image. In particular, apex candidates and base candidates are detected in the 2D MRI image. One of the LV candidates is selected as a final LV detection result using component-based voting based on the detected LV candidates, apex candidates, and base candidates. | 02-18-2010 |
| 20100067760 | Method and System for Automatic Coronary Artery Detection - A method and system for coronary artery detection in 3D cardiac volumes is disclosed. The heart chambers are segmented in the cardiac volume, and an initial estimation of a coronary artery is generated based on the segmented heart chambers. The initial estimation of the coronary artery is then refined based on local information in the cardiac volume in order to detect the coronary artery in the cardiac volume. The detected coronary artery can be extended using 3D dynamic programming. | 03-18-2010 |
| 20100067764 | Method and System for Automatic Landmark Detection Using Discriminative Joint Context - A method and system for detecting anatomic landmarks in medical images is disclosed. In order to detect multiple related anatomic landmarks, a plurality of landmark candidates are first detected individually using trained landmark detectors. A joint context is then generated for each combination of the landmark candidates. The best combination of landmarks in then determined based on the joint context using a trained joint context detector. | 03-18-2010 |
| 20100067768 | Method and System for Physiological Image Registration and Fusion - A method and system for physiological image registration and fusion is disclosed. A physiological model of a target anatomical structure in estimated each of a first image and a second image. The physiological model is estimated using database-guided discriminative machine learning-based estimation. A fused image is then generated by registering the first and second images based on correspondences between the physiological model estimated in each of the first and second images. | 03-18-2010 |
| 20100070249 | Method and System for Generating a Personalized Anatomical Heart Model - A method and system for generating a patient specific anatomical heart model is disclosed. Volumetric image data, such as computed tomography (CT) or echocardiography image data, of a patient's cardiac region is received. Individual models for multiple heart components, such as the left ventricle (LV) endocardium, LV epicardium, right ventricle (RV), left atrium (LA), right atrium (RA), mitral valve, aortic valve, aorta, and pulmonary trunk, are estimated in said volumetric cardiac image data. A patient specific anatomical heart model is generated by integrating the individual models for each of the heart components. | 03-18-2010 |
| 20100076296 | Method and System for Automatic Detection of Coronary Stenosis in Cardiac Computed Tomography Data - 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. | 03-25-2010 |
| 20100142787 | Method and System for Left Ventricle Detection in 2D Magnetic Resonance Images Using Ranking Based Multi-Detector Aggregation - A method and system for left ventricle (LV) detection in 2D magnetic resonance imaging (MRI) images is disclosed. In order to detect the LV in a 2D MRI image, a plurality of LV candidates are detected, for example using marginal space learning (MSL) based detection. Candidates for distinctive anatomic landmarks associated with the LV are then detected in the 2D MRI image. In particular, apex candidates and base candidates are detected in the 2D MRI image. One of the LV candidates is selected as a final LV detection result by ranking the LV candidates based on the LV candidates, the apex candidates, and the base candidates using a trained ranking model. | 06-10-2010 |
| 20100239147 | Method and System for Dynamic Pulmonary Trunk Modeling and Intervention Planning - A method and system for modeling the pulmonary trunk in 4D image data, such as 4D CT data, and model-based percutaneous pulmonary valve implantation (PPVI) intervention is disclosed. A patient-specific dynamic pulmonary trunk data is generated from 4D image data of a patient. The patient is automatically classified as suitable for PPVI intervention or not suitable for PPVI intervention based on the generated patient-specific dynamic pulmonary trunk model. | 09-23-2010 |
| 20100239148 | Method and System for Automatic Aorta Segmentation - 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. | 09-23-2010 |
| 20100240996 | VALVE ASSESSMENT FROM MEDICAL DIAGNOSTIC IMAGING DATA - Heart valve operation is assessed with patient-specific medical diagnostic imaging data. To deal with the complex motion of the passive valve tissue, a hierarchal model is used. Rigid global motion of the overall valve, non-rigid local motion of landmarks of the valve, and surface motion of the valve are modeled sequentially. For the non-rigid local motion, a spectral trajectory approach is used in the model to determine location and motion of the landmarks more efficiently than detection and tracking. Given efficiencies in processing, more than one valve may be modeled at a same time. A graphic overlay representing the valve in four dimensions and/or quantities may be provided during an imaging session. One or more of these features may be used in combination or independently. | 09-23-2010 |
| 20100280352 | Method and System for Multi-Component Heart and Aorta Modeling for Decision Support in Cardiac Disease - A method and system for generating a patient specific anatomical heart model is disclosed. Volumetric image data, such as computed tomography (CT), echocardiography, or magnetic resonance (MR) image data of a patient's cardiac region is received. Individual models for multiple heart components, such as the left ventricle (LV) endocardium, LV epicardium, right ventricle (RV), left atrium (LA), right atrium (RA), mitral valve, aortic valve, aorta, and pulmonary trunk, are estimated in said volumetric cardiac image data. A multi-component patient specific anatomical heart model is generated by integrating the individual models for each of the heart components. Fluid Structure Interaction (FSI) simulations are performed on the patient specific anatomical model, and patient specific clinical parameters are extracted based on the patient specific heart model and the FSI simulations. Disease progression modeling and risk stratification are performed based on the patient specific clinical parameters. | 11-04-2010 |
| 20110060576 | Method and System for Computational Modeling of the Aorta and Heart - A method and system for generating a patient specific anatomical heart model is disclosed. A sequence of volumetric image data, such as computed tomography (CT), echocardiography, or magnetic resonance (MR) image data of a patient's cardiac region is received. A multi-component patient specific 4D geometric model of the heart and aorta estimated from the sequence of volumetric cardiac imaging data. A patient specific 4D computational model based on one or more of personalized geometry, material properties, fluid boundary conditions, and flow velocity measurements in the 4D geometric model is generated. Patient specific material properties of the aortic wall are estimated using the 4D geometrical model and the 4D computational model. Fluid Structure Interaction (FSI) simulations are performed using the 4D computational model and estimated material properties of the aortic wall, and patient specific clinical parameters are extracted based on the FSI simulations. Disease progression modeling and risk stratification are performed based on the patient specific clinical parameters. | 03-10-2011 |
| 20110153286 | Method and System for Virtual Percutaneous Valve Implantation - 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. | 06-23-2011 |
| 20110191283 | Method and System for Medical Decision Support Using Organ Models and Learning Based Discriminative Distance Functions - A method and system for providing medical decision support based on virtual organ models and learning based discriminative distance functions is disclosed. A patient-specific virtual organ model is generated from medical image data of a patient. One or more similar organ models to the patient-specific organ model are retrieved from a plurality of previously stored virtual organ models using a learned discriminative distance function. The patient-specific valve model can be classified into a first class or a second class based on the previously stored organ models determined to be similar to the patient-specific organ model. | 08-04-2011 |
| 20110224542 | Method and System for Automatic Detection and Classification of Coronary Stenoses in Cardiac CT Volumes - 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. | 09-15-2011 |
| 20110301466 | CARDIAC FLOW QUANTIFICATION WITH VOLUMETRIC IMAGING DATA - A method quantifies cardiac volume flow for an imaging sequence. The method includes receiving data representing three-dimensions and color Doppler flow data over a plurality of frames, constructing a ventricular model based on the data representing three-dimensions for the plurality of frames, the ventricular model including a sampling plane configured to measure the cardiac volume flow, computing volume flow samples based on the sampling plane and the color Doppler flow data, and correcting the volume flow samples for aliasing based on volumetric change in the ventricular model between successive frames of the plurality of frames. | 12-08-2011 |
| 20120022843 | Method and System for Comprehensive Patient-Specific Modeling of the Heart - 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. | 01-26-2012 |
| 20120072190 | Method and System for Non-Invasive Assessment of Coronary Artery Disease - A method and system for non-invasive patient-specific assessment of coronary artery disease is disclosed. An anatomical model of a coronary artery is generated from 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. | 03-22-2012 |
| 20120078097 | COMPUTERIZED CHARACTERIZATION OF CARDIAC MOTION IN MEDICAL DIAGNOSTIC ULTRASOUND - Computerized characterization of cardiac wall motion is provided. Quantities for cardiac wall motion are determined from a four-dimensional (i.e., 3D+time) sequence of ultrasound data. A processor automatically processes the volume data to locate the cardiac wall through the sequence and calculate the quantity from the cardiac wall position or motion. Various machine learning is used for locating and tracking the cardiac wall, such as using a motion prior learned from training data for initially locating the cardiac wall and the motion prior, speckle tracking, boundary detection, and mass conservation cues for tracking with another machine learned classifier. Where the sequence extends over multiple cycles, the cycles are automatically divided for independent tracking of the cardiac wall. The cardiac wall from one cycle may be used to propagate to another cycle for initializing the tracking. Independent tracking in each cycle may reduce or avoid inaccuracies due to drift. | 03-29-2012 |
| 20120087563 | Method and System for Intraoperative Guidance Using Physiological Image Fusion - A method and system for intraoperative guidance in an off-pump mitral valve repair procedure is disclosed. A plurality of patient-specific models of the mitral valve are generated, each from pre-operative image data obtained using a separate imaging modality. The pre-operative image data from the separate imaging modalities are fused into a common coordinate system by registering the plurality of patient-specific models. A model of the mitral valve is estimated in real-time in intraoperative image data using a fused physiological prior resulting from the registering of the plurality of patient-specific models. | 04-12-2012 |
| 20120121152 | Method and System for Automatic View Planning for Cardiac Magnetic Resonance Imaging acquisition - A method and system for automated view planning for cardiac magnetic resonance imaging (MRI) acquisition is disclosed. The method and system automatically generate a full scan prescription using a single 3D MRI volume. The left ventricle (LV) is segmented in the 3D MRI volume. Cardiac landmarks are detected in the automatically prescribed slices. A full scan prescription, including a short axis stack and 2-chamber, 3-chamber, and 4-chamber views, is automatically generated based on cardiac anchors provided by the segmented left ventricle and the detected cardiac landmarks in the 3D MRI volume. | 05-17-2012 |
| 20120177269 | Detection of Landmarks and Key-frames in Cardiac Perfusion MRI Using a Joint Spatial-Temporal Context Model - A method including receiving an image sequence, wherein the image sequence includes a plurality of two-dimensional (2D) image frames of an organ arranged in a time sequence; constructing a three-dimensional (3D) volume by stacking a plurality of the 2D image frames in time order; detecting a best bounding box for a target of interest in the 3D volume, wherein the best bounding box is specified by a plurality of parameters including spatial and temporal information contained in the 3D volume; and determining the target of interest from the best bounding box. | 07-12-2012 |
| 20120203530 | Method and System for Patient-Specific Computational Modeling and Simulation for Coupled Hemodynamic Analysis of Cerebral Vessels - A method and system for patient-specific computational modeling and simulation for coupled hemodynamic analysis of cerebral vessels is disclosed. An anatomical model of a cerebral vessel is extracted from 3D medical image data. The anatomical model of the cerebral vessel includes an inner wall and an outer wall of the cerebral vessel. Blood flow in the cerebral vessel and deformation of the cerebral vessel wall are simulated using coupled computational fluid dynamics (CFD) and computational solid mechanics (CSM) simulations based on the anatomical model of the cerebral vessel. | 08-09-2012 |
| 20120230568 | Method and System for Model-Based Fusion of Multi-Modal Volumetric Images - 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. | 09-13-2012 |
| 20120232386 | VALVE TREATMENT SIMULATION FROM MEDICAL DIAGNOSTIC IMAGING DATA - Valve treatment simulation is performed from patient specific imaging data for therapy planning. A model of the valve may be generated from the patient specific data automatically or with very minimal user indication of anatomy locations relative to an image. Any characteristics for the valve not extracted from images of the patient may be added to create a volumetric model. Added characteristics include chordae, such as chordae length and leaflet fiber direction. The characteristics may be adjusted based on user feedback and/or comparison with images of the patient. The effect of therapy on closure of the valve may be simulated from the model. For instance, mitral clip intervention is simulated on the patient-specific model. Valves are deformed according to the clip location. Valve closure is then simulated to predict effect of the therapy in terms of mitral regurgitation. | 09-13-2012 |
| 20120232853 | PHYSICALLY-CONSTRAINED MODELING OF A HEART IN MEDICAL IMAGING - Physically-constrained modeling of a heart is provided. Patient-specific data may be used to estimate heart anatomy locations. A model is applied to the data for estimation. For increased accuracy of estimation, the biomechanics of the heart, such as the valve, may be used to constrain the estimation. By applying a dynamic system between estimated anatomy locations of different times, the locations may be deformed or refined. The modeled heart and/or valve may be used to estimate hemodynamics. The resulting velocities or other motion information may be used to emulate ultrasound Doppler imaging for comparing with acquired ultrasound Doppler data. The comparison may validate the modeling. | 09-13-2012 |
| 20120257807 | Method and System for Detection of Contrast Injection Fluoroscopic Image Sequences - A method and system for detecting a spatial and temporal location of a contrast injection in a fluoroscopic image sequence is disclosed. Training volumes generated by stacking a sequence of 2D fluoroscopic images in time order are annotated with ground truth contrast injection points. A heart rate is globally estimated for each training volume, and local frequency and phase is estimated in a neighborhood of the ground truth contrast injection point for each training volume. Frequency and phase invariant features are extracted from each training volume based on the heart rate, local frequency and phase, and a detector is trained based on the training volumes and the features extracted for each training volume. The detector can be used to detect the spatial and temporal location of a contrast injection in a fluoroscopic image sequence. | 10-11-2012 |
| 20130129173 | Method and System for Intervention Planning for Transcatheter Aortic Valve Implantation from 3D Computed Tomography Data - A method and system for automated intervention planning for transcatheter aortic valve implantations using computed tomography (CT) data is disclosed. A patient-specific aortic valve model is detected in a CT volume of a patient. The patient-specific aortic valve model is detected by detecting a global location of the patient-specific aortic valve model in the CT volume, detecting aortic valve landmarks based on the detected global location, and fitting an aortic root surface model. Angulation parameters of a C-arm imaging device for acquiring intra-operative fluoroscopic images and anatomical measurements of the aortic valve are automatically determined based on the patient-specific aortic valve model. | 05-23-2013 |
| 20130132054 | Method and System for Multi-Scale Anatomical and Functional Modeling of Coronary Circulation - A method and system for multi-scale anatomical and functional modeling of coronary circulation is disclosed. A patient-specific anatomical model of coronary arteries and the heart is generated from medical image data of a patient. A multi-scale functional model of coronary circulation is generated based on the patient-specific anatomical model. Blood flow is simulated in at least one stenosis region of at least one coronary artery using the multi-scale function model of coronary circulation. Hemodynamic quantities, such as fractional flow reserve (FFR), are computed to determine a functional assessment of the stenosis, and virtual intervention simulations are performed using the multi-scale function model of coronary circulation for decision support and intervention planning. | 05-23-2013 |
| 20130144161 | Flow Quantification in Ultrasound Using Conditional Random Fields with Global Consistency - Velocities are unaliased using conditional random fields. To constrain the energy minimization function, a global term includes a measure of a level of aliasing. In one example, the measure of the level of aliasing is based on a change in volume, such as the volume of the left ventricle. The unaliasing is performed along one or more surfaces, such as surfaces intersecting the mitral annulus and the left ventricle outflow tract. The anatomy used is identified and/or tracked using one or more machine-learnt detectors. Both B-mode and velocity information may be used for detecting the anatomy. | 06-06-2013 |
| 20130144573 | Method and System for Patient-Specific Hemodynamic Assessment of Virtual Stent Implantation - A method and system for assessment of virtual stent implantation in an aortic aneurysm is disclosed. A patient-specific 4D anatomical model of the aorta is generated from the 4D medical imaging data. A model representing mechanical properties of the aorta wall is adjusted to reflect changes due to aneurysm growth at a plurality of time stages. A stable deformation configuration of the aorta is generated for each time stages by performing fluid structure interaction (FSI) simulations using the patient-specific 4D anatomical model at each time stage based on the adjusted model representing the mechanical properties of the aorta wall at each time stage. Virtual stent implantation is performed for each stable deformation configuration of the aorta and FSI simulations are performed for each virtual stent implantation. | 06-06-2013 |
| 20130197881 | Method and System for Patient Specific Planning of Cardiac Therapies on Preoperative Clinical Data and Medical Images - 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. | 08-01-2013 |
| 20130197884 | Method and System for Advanced Measurements Computation and Therapy Planning from Medical Data and Images Using a Multi-Physics Fluid-Solid Heart Model - Method and system for computation of advanced heart measurements from medical images and data; and therapy planning using a patient-specific multi-physics fluid-solid heart model is disclosed. A patient-specific anatomical model of the left and right ventricles is generated from medical image patient data. A patient-specific computational heart model is generated based on the patient-specific anatomical model of the left and right ventricles and patient-specific clinical data. The computational model includes biomechanics, electrophysiology and hemodynamics. To generate the patient-specific computational heart model, initial patient-specific parameters of an electrophysiology model, initial patient-specific parameters of a biomechanics model, and initial patient-specific computational fluid dynamics (CFD) boundary conditions are marginally estimated. A coupled fluid-structure interaction (FSI) simulation is performed using the initial patient-specific parameters, and the initial patient-specific parameters are refined based on the coupled FSI simulation. The estimated model parameters then constitute new advanced measurements that can be used for decision making. | 08-01-2013 |
| 20130226542 | Method and System for Fast Patient-Specific Cardiac Electrophysiology Simulations for Therapy Planning and Guidance - A method and system for patient-specific cardiac electrophysiology is disclosed. Particularly, a patient-specific anatomical model of a heart is generated from medical image data of a patient, a level-set representation of the patient-specific anatomical model is generated of the heart on a Cartesian grid; and a transmembrane action potential at each node of the level-set representation of the of the patient-specific anatomical model of the heart is computed on a Cartesian grid. | 08-29-2013 |
| 20130246034 | Method and System for Non-Invasive Functional Assessment of Coronary Artery Stenosis - A method and system for non-invasive assessment of coronary artery stenosis is disclosed. Patient-specific anatomical measurements of the coronary arteries are extracted from medical image data of a patient acquired during rest state. Patient-specific rest state boundary conditions of a model of coronary circulation representing the coronary arteries are calculated based on the patient-specific anatomical measurements and non-invasive clinical measurements of the patient at rest. Patient-specific rest state boundary conditions of the model of coronary circulation representing the coronary arteries are calculated based on the patient-specific anatomical measurements and non-invasive clinical measurements of the patient at rest. Hyperemic blood flow and pressure across at least one stenosis region of the coronary arteries are simulated using the model of coronary circulation and the patient-specific hyperemic boundary conditions. Fractional flow reserve (FFR) is calculated for the at least one stenosis region based on the simulated hyperemic blood flow and pressure. | 09-19-2013 |
| 20130324841 | System and Method for Real-Time Ultrasound Guided Prostate Needle Biopsy Based on Biomechanical Model of the Prostate from Magnetic Resonance Imaging Data - 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. | 12-05-2013 |
| 20140012558 | SYSTEM AND METHODS FOR INTEGRATED AND PREDICTIVE ANALYSIS OF MOLECULAR, IMAGING, AND CLINICAL DATA FOR PATIENT-SPECIFIC MANAGEMENT OF DISEASES - 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. | 01-09-2014 |
| 20140022250 | System and Method for Patient Specific Planning and Guidance of Ablative Procedures for Cardiac Arrhythmias - A method and system for patient-specific planning and guidance of an ablation procedure for cardiac arrhythmia is disclosed. A patient-specific anatomical heart model is generated based on pre-operative cardiac image data. The patient-specific anatomical heart model is registered to a coordinate system of intra-operative images acquired during the ablation procedure. One or more ablation site guidance maps are generated based on the registered patient-specific anatomical heart model and intra-operative patient-specific measurements acquired during the ablation procedure. The ablation site guidance maps may include myocardium diffusion and action potential duration maps. The ablation site guidance maps are generated using a computational model of cardiac electrophysiology which is personalized by fitting parameters of the cardiac electrophysiology model using the intra-operative patient-specific measurements. The ablation site guidance maps are displayed by a display device during the ablation procedure. | 01-23-2014 |
| 20140024932 | Computation of Hemodynamic Quantities From Angiographic Data - Methods for computing hemodynamic quantities include: (a) acquiring angiography data from a patient; (b) calculating a flow and/or calculating a change in pressure in a blood vessel of the patient based on the angiography data; and (c) computing the hemodynamic quantity based on the flow and/or the change in pressure. Systems for computing hemodynamic quantities and computer readable storage media are described. | 01-23-2014 |
| 20140052001 | Mitral Valve Detection for Transthoracic Echocardiography - 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. | 02-20-2014 |
| 20140058715 | Method and System for Non-Invasive Functional Assessment of Coronary Artery Stenosis - A method and system for non-invasive assessment of coronary artery stenosis is disclosed. Patient-specific anatomical measurements of the coronary arteries are extracted from medical image data of a patient acquired during rest state. Patient-specific rest state boundary conditions of a model of coronary circulation representing the coronary arteries are calculated based on the patient-specific anatomical measurements and non-invasive clinical measurements of the patient at rest. Patient-specific rest state boundary conditions of the model of coronary circulation representing the coronary arteries are calculated based on the patient-specific anatomical measurements and non-invasive clinical measurements of the patient at rest. Hyperemic blood flow and pressure across at least one stenosis region of the coronary arteries are simulated using the model of coronary circulation and the patient-specific hyperemic boundary conditions. Fractional flow reserve (FFR) is calculated for the at least one stenosis region based on the simulated hyperemic blood flow and pressure. | 02-27-2014 |
| 20140207715 | DATA DRIVEN REDUCTION OF MULTI-SCALE MODELS - A method of computing physiological measurements resulting from a multi-scale physiological system using a data-driven model includes generating a database of physiological measurements associated with a multi-scale physiological system. A computer uses dimensionality reduction techniques on the database to identify a reduced set of components explaining the multi-scale physiological system. The computer learns a data-driven model of the multi-scale physiological system from the database. Then, new input parameters are received by the computer and used to compute new physiological measurements using the data-driven model. New derived physiological indicators are computed by the computer based on the reduced set of components. Once computed, the new derived physiological indicators may be displayed along with the new physiological measurements. | 07-24-2014 |
| 20150042646 | System and Method for Patient Specific Planning and Guidance of Electrophysiology Interventions - A method and system for patient-specific planning and guidance of electrophysiological interventions is disclosed. A patient-specific anatomical heart model is generated from cardiac image data of a patient. A patient-specific cardiac electrophysiology model is generated based on the patient-specific anatomical heart model and patient-specific electrophysiology measurements. Virtual electrophysiological interventions are performed using the patient-specific cardiac electrophysiology model. A simulated electrocardiogram (ECG) signal is calculated in response to each virtual electrophysiological intervention. | 02-12-2015 |
| 20150045644 | System and Method for Estimating Artery Compliance and Resistance from 4D Cardiac Images and Pressure Measurements - A method and system for estimating arterial compliance and resistance based on medical image data and pressure measurements is disclosed. An arterial inflow estimate over a plurality of time points is determined based on medical image data of a patient. An arterial pressure measurement of the patient is received. At least one cardiac cycle of the arterial pressure measurement is synchronized with at least one cardiac cycle of the arterial inflow measurement. Arterial compliance and resistance of the patient is estimated based on the arterial inflow estimate and the synchronized arterial pressure measurement. | 02-12-2015 |
