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Leo Grady, Millbrae US

Leo Grady, Millbrae, CA US

Patent application numberDescriptionPublished
20130077842Semi-Automated Preoperative Resection Planning - Preoperative resection planning is assisted by a computer. Rather than rely on interpolation of the user input, a graph of interconnections is used. The user inputs one or more polylines on one or more two-dimensional views. The polylines are used to assign resection and remnant seeds with a band of unassigned locations. The 2D seeds are used with the graph of interconnections to assign different voxels in the volume, including the unassigned locations, as being part of the resection volume or part of the remnant volume.03-28-2013
20130088225System for Reconstructing MRI Images Acquired in Parallel - A system for parallel image processing in MR imaging comprises multiple MR imaging RF coils for individually receiving MR imaging data representing a slice of patient anatomy. An MR imaging system uses the multiple RF coils for acquiring corresponding multiple image data sets of the slice. An image data processor comprises at least one processing device conditioned for, deriving a first set of weights for generating a calibration data set comprising a subset of k-space data of composite image data representing the multiple image data sets. The at least one processing device uses the calibration data set in generating a first MR image data set, deriving a second set of weights using the calibration data set and the generated first MR image data set and uses the second set of weights in generating a second MR image data set representing a single image having a reduced set of data components relative to the first composite MR image data set.04-11-2013
20130207652System for Accelerated Magnetic Resonance Imaging Using Parallel Coils - An MR imaging system uses multiple RF coils for acquiring corresponding multiple image data sets of a slice or volume of patient anatomy. An image data processor comprises at least one processing device conditioned for, deriving a first set of weights for weighted combination of k-space data of the multiple image data sets for generating a calibration data set comprising a subset of k-space data of composite image data representing the multiple image data sets. The image data processor uses the calibration data set in generating a first MR image data set, deriving the parameters of a probability distribution in response to the first set of weights and the first MR image data set and deriving a second set of weights and second MR image data set together using the probability distribution.08-15-2013
20130231552Method and System for Diagnosis of Attention Deficit Hyperactivity Disorder from Magnetic Resonance Images - A method and system for automated diagnosis of attention deficit hyperactivity disorder (ADHD) from magnetic resonance images is disclosed. Anatomical features are extracted from a structural magnetic resonance image (MRI) of a patient. Functional features are extracted from a resting-state functional MRI (rsFMRI) series of the patient. An ADHD diagnosis for the patient is determined based on the anatomical features, the functional features, and phenotypic features of the patient using a trained classifier. An ADHD subtype may then be determined for patients diagnosed as ADHD positive using a second trained classifier.09-05-2013
20130243352Global Error Minimization In Image Mosaicking Using Graph Laplacians And Its Applications In Microscopy - An image mosaicking method includes performing pairwise registration of a plurality of tiles (09-19-2013
20130272587SYSTEM AND METHOD FOR INTERACTIVE SEGMENTATION ON MOBILE DEVICES IN A CLOUD COMPUTING ENVIRONMENT - A mobile device (10-17-2013
20140073976SYSTEMS AND METHODS FOR ESTIMATING ISCHEMIA AND BLOOD FLOW CHARACTERISTICS FROM VESSEL GEOMETRY AND PHYSIOLOGY - Systems and methods are disclosed for determining individual-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the individual-specific anatomic data and blood flow characteristics for each of the plurality of individuals; relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics; acquiring, for an individual and individual-specific anatomic data of at least part of the individual's vascular system; and for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics.03-13-2014
20140073977SYSTEMS AND METHODS FOR ESTIMATING BLOOD FLOW CHARACTERISTICS FROM VESSEL GEOMETRY AND PHYSIOLOGY - Systems and methods are disclosed for estimating patient-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, a geometric model and estimated blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the geometric model and estimated blood flow characteristics for each of the plurality of individuals; identifying, using the machine learning algorithm, features predictive of blood flow characteristics corresponding to a plurality of points in the geometric models; acquiring, for a patient, a geometric model of at least part of the patient's vascular system; and using the identified features to produce estimates of the patient's blood flow characteristic for each of a plurality of points in the patient's geometric model.03-13-2014
20140133733Cell Feature-Based Automatic Circulating Tumor Cell Detection - An automated method for detecting circulating tumor cells in a microscopic image of a blood sample includes receiving, by a computer, a plurality of low-resolution images, each low resolution image providing a representation of the blood sample with one of a plurality of stains applied. The computer determines a threshold value for each of the plurality of stains based on the low resolution images and identifies a list of potential cells based on the threshold values. A gating process is performed on the list of potential circulating tumor cells to identify one or more likely or highly likely circulating tumor cells. The computer presents the subset of the low-resolution images in a verification interface comprising one or more components allowing a user to confirm that a respective low-resolution image included in the subset of the low-resolution images includes one or more circulating tumor cells.05-15-2014
20140221832TUNING ULTRASOUND ACQUISITION PARAMETERS - Values for ultrasound acquisition parameters are altered in a manifold space. The number of parameters to be set is reduced using a manifold. Virtual parameters different than the acquisition parameters are used to alter the greater number of acquisition parameters. In a further use, optimum image settings may be obtained in an automated system by measuring image quality for feeding back to virtual parameter adjustment.08-07-2014
20140249784METHOD AND SYSTEM FOR SENSITIVITY ANALYSIS IN MODELING BLOOD FLOW CHARACTERISTICS - Embodiments include systems and methods for determining cardiovascular information for a patient. A method includes receiving patient-specific data regarding a geometry of the patient's vasculature; creating an anatomic model representing at least a portion of the patient's vasculature based on the patient-specific data; and creating a computational model of a blood flow characteristic based on the anatomic model. The method also includes identifying one or more of an uncertain parameter, an uncertain clinical variable, and an uncertain geometry; modifying a probability model based on one or more of the identified uncertain parameter, uncertain clinical variable, or uncertain geometry; determining a blood flow characteristic within the patient's vasculature based on the anatomic model and the computational model of the blood flow characteristic of the patient's vasculature; and calculating, based on the probability model and the determined blood flow characteristic, a sensitivity of the determined fractional flow reserve to one or more of the identified uncertain parameter, uncertain clinical variable, or uncertain geometry.09-04-2014
20140249790METHOD AND SYSTEM FOR DETERMINING TREATMENTS BY MODIFYING PATIENT-SPECIFIC GEOMETRICAL MODELS - Systems and methods are disclosed for evaluating cardiovascular treatment options for a patient. One method includes creating a three-dimensional model representing a portion of the patient's heart based on patient-specific data regarding a geometry of the patient's heart or vasculature; and for a plurality of treatment options for the patient's heart or vasculature, modifying at least one of the three-dimensional model and a reduced order model based on the three-dimensional model. The method also includes determining, for each of the plurality of treatment options, a value of a blood flow characteristic, by solving at least one of the modified three-dimensional model and the modified reduced order model; and identifying one of the plurality of treatment options that solves a function of at least one of: the determined blood flow characteristics of the patient's heart or vasculature, and one or more costs of each of the plurality of treatment options.09-04-2014
20140314292METHOD AND SYSTEM FOR INTEGRATED RADIOLOGICAL AND PATHOLOGICAL INFORMATION FOR DIAGNOSIS, THERAPY SELECTION, AND MONITORING - A method and system for integrating radiological and pathological information for cancer diagnosis, therapy selection, and monitoring is disclosed. A radiological image of a patient, such as a magnetic resonance (MR), computed tomography (CT), positron emission tomography (PET), or ultrasound image, is received. A location corresponding to each of one or more biopsy samples is determined in the at least one radiological image. An integrated display is used to display a histological image corresponding to the each biopsy samples, the radiological image, and the location corresponding to each biopsy samples in the radiological image. Pathological information and radiological information are integrated by combining features extracted from the histological images and the features extracted from the corresponding locations in the radiological image for cancer grading, prognosis prediction, and therapy selection.10-23-2014
20140372096METHOD AND SYSTEM FOR DETERMINING TREATMENTS BY MODIFYING PATIENT-SPECIFIC GEOMETRICAL MODELS - Systems and methods are disclosed for evaluating cardiovascular treatment options for a patient. One method includes creating a three-dimensional model representing a portion of the patient's heart based on patient-specific data regarding a geometry of the patient's heart or vasculature; and for a plurality of treatment options for the patient's heart or vasculature, modifying at least one of the three-dimensional model and a reduced order model based on the three-dimensional model. The method also includes determining, for each of the plurality of treatment options, a value of a blood flow characteristic, by solving at least one of the modified three-dimensional model and the modified reduced order model; and identifying one of the plurality of treatment options that solves a function of at least one of: the determined blood flow characteristics of the patient's heart or vasculature, and one or more costs of each of the plurality of treatment options.12-18-2014
20140379318METHOD AND SYSTEM FOR DETERMINING TREATMENTS BY MODIFYING PATIENT-SPECIFIC GEOMETRICAL MODELS - Systems and methods are disclosed for evaluating cardiovascular treatment options for a patient. One method includes creating a three-dimensional model representing a portion of the patient's heart based on patient-specific data regarding a geometry of the patient's heart or vasculature; and for a plurality of treatment options for the patient's heart or vasculature, modifying at least one of the three-dimensional model and a reduced order model based on the three-dimensional model. The method also includes determining, for each of the plurality of treatment options, a value of a blood flow characteristic, by solving at least one of the modified three-dimensional model and the modified reduced order model; and identifying one of the plurality of treatment options that solves a function of at least one of: the determined blood flow characteristics of the patient's heart or vasculature, and one or more costs of each of the plurality of treatment options.12-25-2014
20150051884SYSTEMS AND METHODS FOR IDENTIFYING PERSONALIZED VASCULAR IMPLANTS FROM PATIENT-SPECIFIC ANATOMIC DATA - Embodiments include methods of identifying a personalized cardiovascular device based on patient-specific geometrical information, the method comprising acquiring an anatomical model of at least part of the patient's vascular system; performing, using a processor, one or more of geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis on the anatomical model; and identifying, using the processor, a personalized cardiovascular device for the patient, based on results of one or more of the geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis of anatomical model.02-19-2015
20150051885SYSTEMS AND METHODS FOR IDENTIFYING PERSONALIZED VASCULAR IMPLANTS FROM PATIENT-SPECIFIC ANATOMIC DATA - Embodiments include methods of identifying a personalized cardiovascular device based on patient-specific geometrical information, the method comprising acquiring a geometric model of at least a portion of a patient's vascular system; obtaining one or more geometric quantities of one or more blood vessels of the geometric model of the patient's vascular system; determining the presence or absence of a pathology characteristic at a location in the geometric model of the patient's vascular system; generating an objective function defined by a plurality of device variables and a plurality of hemodynamic and solid mechanics characteristics; and optimizing the objective function using computational fluid dynamics and structural mechanics analysis to identify a plurality of device variables that result in desired hemodynamic and solid mechanics characteristics.02-19-2015
20150051886SYSTEMS AND METHODS FOR IDENTIFYING PERSONALIZED VASCULAR IMPLANTS FROM PATIENT-SPECIFIC ANATOMIC DATA - Embodiments include methods of identifying a personalized cardiovascular device based on patient-specific geometrical information, the method comprising: generating a patient specific model of at least a portion of a patient's vasculature from image data of the patient's vasculature and one or more measured or estimated physiological or phenotypic parameters of the patient; determining pathology characteristics from cardiovascular geometry of the patient specific model; defining an objective function for a device based on design considerations and one or more estimates of hemodynamic and mechanical characteristics; optimizing the objective function, by simulating at least one change in devices and evaluating the objective function using fluid dynamic or structural mechanic analyses; and using the optimized objective function to either (i) select a device from a set of available devices or (ii) manufacture a desired device.02-19-2015
20150065846SYSTEMS AND METHODS FOR PREDICTING LOCATION, ONSET, AND/OR CHANGE OF CORONARY LESIONS - Systems and methods are disclosed for predicting the location, onset, or change of coronary lesions from factors like vessel geometry, physiology, and hemodynamics. One method includes: acquiring, for each of a plurality of individuals, a geometric model, blood flow characteristics, and plaque information for part of the individual's vascular system; training a machine learning algorithm based on the geometric models and blood flow characteristics for each of the plurality of individuals, and features predictive of the presence of plaque within the geometric models and blood flow characteristics of the plurality of individuals; acquiring, for a patient, a geometric model and blood flow characteristics for part of the patient's vascular system; and executing the machine learning algorithm on the patient's geometric model and blood flow characteristics to determine, based on the predictive features, plaque information of the patient for at least one point in the patient's geometric model.03-05-2015
20150065847SYSTEMS AND METHODS FOR PREDICTING LOCATION, ONSET, AND/OR CHANGE OF CORONARY LESIONS - Systems and methods are disclosed for predicting the location, onset, or change of coronary lesions from factors like vessel geometry, physiology, and hemodynamics. One method includes: acquiring, for each of a plurality of individuals, a geometric model, blood flow characteristics, and plaque information for part of the individual's vascular system; training a machine learning algorithm based on the geometric models and blood flow characteristics for each of the plurality of individuals, and features predictive of the presence of plaque within the geometric models and blood flow characteristics of the plurality of individuals; acquiring, for a patient, a geometric model and blood flow characteristics for part of the patient's vascular system; and executing the machine learning algorithm on the patient's geometric model and blood flow characteristics to determine, based on the predictive features, plaque information of the patient for at least one point in the patient's geometric model.03-05-2015
20150065848SYSTEMS AND METHODS FOR PREDICTING LOCATION, ONSET, AND/OR CHANGE OF CORONARY LESIONS - Systems and methods are disclosed for predicting the location, onset, or change of coronary lesions from factors like vessel geometry, physiology, and hemodynamics. One method includes: acquiring, for each of a plurality of individuals, a geometric model, blood flow characteristics, and plaque information for part of the individual's vascular system; training a machine learning algorithm based on the geometric models and blood flow characteristics for each of the plurality of individuals, and features predictive of the presence of plaque within the geometric models and blood flow characteristics of the plurality of individuals; acquiring, for a patient, a geometric model and blood flow characteristics for part of the patient's vascular system; and executing the machine learning algorithm on the patient's geometric model and blood flow characteristics to determine, based on the predictive features, plaque information of the patient for at least one point in the patient's geometric model.03-05-2015
20150066818SYSTEMS AND METHODS FOR PREDICTING LOCATION, ONSET, AND/OR CHANGE OF CORONARY LESIONS - Systems and methods are disclosed for predicting the location, onset, or change of coronary lesions from factors like vessel geometry, physiology, and hemodynamics. One method includes: acquiring, for each of a plurality of individuals, a geometric model, blood flow characteristics, and plaque information for part of the individual's vascular system; training a machine learning algorithm based on the geometric models and blood flow characteristics for each of the plurality of individuals, and features predictive of the presence of plaque within the geometric models and blood flow characteristics of the plurality of individuals; acquiring, for a patient, a geometric model and blood flow characteristics for part of the patient's vascular system; and executing the machine learning algorithm on the patient's geometric model and blood flow characteristics to determine, based on the predictive features, plaque information of the patient for at least one point in the patient's geometric model.03-05-2015
20150086133SYSTEMS AND METHODS FOR CONTROLLING USER REPEATABILITY AND REPRODUCIBILITY OF AUTOMATED IMAGE ANNOTATION CORRECTION - Systems and methods are disclosed for controlling image annotation. One method includes acquiring a digital representation of image data and generating a set of image annotations for the digital representation of the image data. The method also may include determining an association between members of the set of image annotations and generating one or more groups of members based on the association. A representative annotation from the one or more groups may also be determined, presented for selection, and the selection may be recorded in memory.03-26-2015

Patent applications by Leo Grady, Millbrae, CA US

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