Patents by Inventor Ali Kamen

Ali Kamen has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10402535
    Abstract: A method and system for personalized computation of tissue ablation extent based on medical images of a patient is disclosed. A patient-specific anatomical model of the liver and liver vessels is estimated from medical image data of a patient. Blood flow in the liver and liver vessels is simulated. An ablation simulation is performed that uses a bio-heat model to simulate heat diffusion due to an ablation based on the simulated blood flow and a cellular necrosis model to simulate cellular necrosis in the liver based on the simulated heat diffusion. Personalized tissue parameters of the bio-heat model and the cellular necrosis model are estimated based on observed results of a preliminary ablation procedure. Planning of the ablation procedure is then performed using the personalized bio-heat equation and the cellular necrosis model. The model can be subsequently refined as more ablation observations are obtained.
    Type: Grant
    Filed: February 13, 2015
    Date of Patent: September 3, 2019
    Assignees: Siemens Healthcare GmbH, Institut National de Recherche en Informatique et en Automatique
    Inventors: Chloe Audigier, Tommaso Mansi, Saikiran Rapaka, Ali Kamen, Viorel Mihalef, Herve Delingette, Nicholas Ayache, Dorin Comaniciu
  • Patent number: 10368850
    Abstract: Systems and methods are provided for utilizing an MRI image and real-time an ultrasound images to guide and/or restrict the movement of an ultrasound probe in position for collecting a biopsy core. A real-time ultrasound image is acquired and fused with pre-operative imaging modalities, such as an MRI image, to provide a three-dimensional model of the prostate. A multi-link robotic arm is provided with an end-effector and an ultrasound probe mounted thereto. Sensor information is used to track the ultrasound probe position with respect to the 3D model. The robotic arm allows for the implementation of a virtual remote center of motion (VRCM) about the transrectal probe tip, an adjustable compliant mode for the physician triggered movement of probe, a restrictive trajectory of joints of the robotic arm and active locking for stationary imaging of the prostate.
    Type: Grant
    Filed: June 18, 2015
    Date of Patent: August 6, 2019
    Assignee: Siemens Medical Solutions USA, Inc.
    Inventors: Ali Kamen, John Benson, Richard Chiao, Dorin Comaniciu, Ankur Kapoor, Yuehaw Khoo, Andrzej Milkowski
  • Patent number: 10373700
    Abstract: 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.
    Type: Grant
    Filed: March 11, 2013
    Date of Patent: August 6, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Puneet Sharma, Lucian Mihai Itu, Ali Kamen, Bogdan Georgescu, Xudong Zheng, Huseyin Tek, Dorin Comaniciu, Dominik Bernhardt, Fernando Vega-Higuera, Michael Scheuering
  • Patent number: 10354744
    Abstract: 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.
    Type: Grant
    Filed: November 4, 2013
    Date of Patent: July 16, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Puneet Sharma, Michael Scheuering, Lucian Mihai Itu, Ali Kamen, Bogdan Georgescu, Xudong Zheng, Huseyin Tek, Dorin Comaniciu, Dominik Bernhardt, Fernando Vega-Higuera
  • Patent number: 10342620
    Abstract: A method for guiding electrophysiology (EP) intervention using a patient-specific electrophysiology model includes acquiring a medical image of a patient subject (S201). Sparse EP signals are acquired over an anatomy using the medical image for guidance (S202). The sparse EP signals are interpolated using a patient specific computational electrophysiology model and a three-dimensional model of EP dynamics is generated therefrom (S203). A rendering of the three-dimensional model is displayed. Candidate intervention sites are received, effects on the EP dynamics resulting from intervention at the candidate intervention sites is simulated using the model, and a rendering of the model showing the simulated effects is displayed (S205).
    Type: Grant
    Filed: April 9, 2015
    Date of Patent: July 9, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Atilla Peter Kiraly, Tommaso Mansi, Ali Kamen
  • Publication number: 20190200880
    Abstract: A method and system for determining fractional flow reserve (FFR) for a coronary artery stenosis of a patient is disclosed. In one embodiment, medical image data of the patient including the stenosis is received, a set of features for the stenosis is extracted from the medical image data of the patient, and an FFR value for the stenosis is determined based on the extracted set of features using a trained machine-learning based mapping. In another embodiment, a medical image of the patient including the stenosis of interest is received, image patches corresponding to the stenosis of interest and a coronary tree of the patient are detected, an FFR value for the stenosis of interest is determined using a trained deep neural network regressor applied directly to the detected image patches.
    Type: Application
    Filed: March 4, 2019
    Publication date: July 4, 2019
    Inventors: Puneet Sharma, Ali Kamen, Bogdan Georgescu, Frank Sauer, Dorin Comaniciu, Yefeng Zheng, Hien Nguyen, Vivek Kumar Singh
  • Patent number: 10335238
    Abstract: A method and system for patient-specific simulation of cardiac electrophysiology is disclosed. A patient-specific anatomical heart model is generated from medical image data of a patient. A patient-specific cardiac electrophysiology model is generated based on simulated torso potentials and body surface potential measurements of the patient. Cardiac electrophysiology of the patient is simulated over time for the patient-specific anatomical heart model using the patient-specific electrophysiology model. One or more electrophysiology maps are generated based on the cardiac electrophysiology simulated using the patient-specific cardiac electrophysiology model.
    Type: Grant
    Filed: March 27, 2015
    Date of Patent: July 2, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Ali Kamen, Tommaso Mansi, Tiziano Passerini, Bogdan Georgescu, Saikiran Rapaka, Dorin Comaniciu, Gabriel Haras
  • Publication number: 20190197199
    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.
    Type: Application
    Filed: January 30, 2013
    Publication date: June 27, 2019
    Applicants: Siemens Aktiengesellschaft, Siemens Corporation
    Inventors: Tommaso Mansi, Bogdan Georgescu, Xudong Zheng, Ali Kamen, Dorin Comaniciu
  • Publication number: 20190195774
    Abstract: The present invention relates to an improved method for marker-free detection of a cell type of at least one cell in a medium using microfluidics and digital holographic microscopy, as well as a device, particular for carrying out the method.
    Type: Application
    Filed: January 26, 2017
    Publication date: June 27, 2019
    Inventors: Noha Youssry El-Zehiry, Oliver Hayden, Ali Kamen, Lukas Richter, Manfred Stanzel, Matthias Ugele, Daniela Seidel, Gaby Marquardt, Oliver Schmidt
  • Patent number: 10325686
    Abstract: 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.
    Type: Grant
    Filed: June 27, 2013
    Date of Patent: June 18, 2019
    Assignees: Siemens Healthcare GmbH, SIEMENS AG OSTERREICH
    Inventors: Tommaso Mansi, Wei Keat Lim, Vanessa King, Andreas Kremer, Bogdan Georgescu, Xudong Zheng, Ali Kamen, Andreas Keller, Cord Friedrich Staehler, Emil Wirsz, Dorin Comaniciu
  • Patent number: 10311978
    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.
    Type: Grant
    Filed: January 30, 2013
    Date of Patent: June 4, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Tommaso Mansi, Bogdan Georgescu, Xudong Zheng, Ali Kamen, Dorin Comaniciu
  • Patent number: 10299862
    Abstract: A medical system is provided for three-dimensional hemodynamic quantification. Comprehensive three-dimensional (3D) plus time (3D+t) assessment of flow patterns inside the heart are provided by a combination of lumped-parameter modeling and computational flow dynamic modeling. Using medical scanning, the lumped parameter model is personalized to a given patient. The personalized lumped-parameter model provides pressure curves (i.e., pressure as a function of time) for one or more locations. Using geometry of the patients heart segmented from the medical scanning and the pressure curves as boundary conditions, the computational flow dynamics model calculates the absolute pressure for any location (e.g., for a three-dimensional field of locations) in the patient heart at any one or more phases of the cardiac cycle. More accurate absolute pressure may be provided without invasive measurement.
    Type: Grant
    Filed: February 5, 2016
    Date of Patent: May 28, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Bogdan Georgescu, Lucian Mihai Itu, Ali Kamen, Tommaso Mansi, Viorel Mihalef, Tiziano Passerini, Rapaka Saikiran, Puneet Sharma
  • Patent number: 10296707
    Abstract: A method and system for image-based patient-specific guidance of cardiac arrhythmia therapies is disclosed. A patient-specific anatomical heart model is generated from medical image data of a patient. A patient-specific cardiac electrophysiology model is generated based on the patient-specific anatomical heart model and electrophysiology measurements of the patient. One or more virtual electrophysiological interventions are performed using the patient-specific cardiac electrophysiology model. One or more pacing targets or ablation targets based on the one or more virtual electrophysiological interventions are displayed.
    Type: Grant
    Filed: April 10, 2015
    Date of Patent: May 21, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Tiziano Passerini, Tommaso Mansi, Ali Kamen, Bogdan Georgescu, Dorin Comaniciu
  • Patent number: 10296809
    Abstract: 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.
    Type: Grant
    Filed: February 28, 2013
    Date of Patent: May 21, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Saikiran Rapaka, Tommaso Mansi, Bogdan Georgescu, Ali Kamen, Dorin Comaniciu
  • Patent number: 10297341
    Abstract: A method for modeling a blood vessel includes: (a) modeling a first segment of the blood vessel based on medical imaging data acquired from a subject; (b) computing a first modeling parameter at an interior point of the first segment; and (c) computing a second modeling parameter at a boundary point of the first segment using a viscoelastic wall model. Systems for modeling a blood vessel are described.
    Type: Grant
    Filed: September 12, 2013
    Date of Patent: May 21, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Lucian Mihai Itu, Puneet Sharma, Ali Kamen, Dorin Comaniciu
  • Patent number: 10282588
    Abstract: Machine training and application of machine-trained classifier are used for image-based tumor phenotyping in a medical system. To create a training database with known phenotype information, synthetic medical images are created. A computational tumor model creates various examples of tumors in tissue. Using the computational tumor model allows one to create examples not available from actual patients, increasing the number and variance of examples used for machine-learning to predict tumor phenotype. A model of an imaging system generates synthetic images from the examples. The machine-trained classifier is applied to images from actual patients to predict tumor phenotype for that patient based on the knowledge learned from the synthetic images.
    Type: Grant
    Filed: May 2, 2017
    Date of Patent: May 7, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Dorin Comaniciu, Ali Kamen, David Liu, Boris Mailhe, Tommaso Mansi
  • Patent number: 10258244
    Abstract: A method and system for determining fractional flow reserve (FFR) for a coronary artery stenosis of a patient is disclosed. In one embodiment, medical image data of the patient including the stenosis is received, a set of features for the stenosis is extracted from the medical image data of the patient, and an FFR value for the stenosis is determined based on the extracted set of features using a trained machine-learning based mapping. In another embodiment, a medical image of the patient including the stenosis of interest is received, image patches corresponding to the stenosis of interest and a coronary tree of the patient are detected, an FFR value for the stenosis of interest is determined using a trained deep neural network regressor applied directly to the detected image patches.
    Type: Grant
    Filed: April 20, 2018
    Date of Patent: April 16, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Puneet Sharma, Ali Kamen, Bogdan Georgescu, Frank Sauer, Dorin Comaniciu, Yefeng Zheng, Hien Nguyen, Vivek Kumar Singh
  • Patent number: 10241968
    Abstract: A method and system for simulating patient-specific cardiac electrophysiology including the effect of the electrical conduction system of the heart is disclosed. A patient-specific anatomical heart model is generated from cardiac image data of a patient. The electrical conduction system of the heart of the patient is modeled by determining electrical diffusivity values of cardiac tissue based on a distance of the cardiac tissue from the endocardium. A distance field from the endocardium surface is calculated with sub-grid accuracy using a nested-level set approach. Cardiac electrophysiology for the patient is simulated using a cardiac electrophysiology model with the electrical diffusivity values determined to model the Purkinje network of the patient.
    Type: Grant
    Filed: February 17, 2015
    Date of Patent: March 26, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Tiziano Passerini, Tommaso Mansi, Ali Kamen, Bogdan Georgescu, Saikiran Rapaka, Dorin Comaniciu
  • Publication number: 20190087638
    Abstract: A method for analyzing digital holographic microscopy (DHM) data for hematology applications includes receiving a plurality of DHM images acquired using a digital holographic microscopy system. One or more connected components are identified in each of the plurality of DHM images and one or more training white blood cell images are generated from the one or more connected components. A classifier is trained to identify a plurality of white blood cell types using the one or more training white blood cell images. The classifier may be applied to a new white blood cell image to determine a plurality of probability values, each respective probability value corresponding to one of the plurality of white blood cell types. The new white blood cell image and the plurality of probability values may then be presented in a graphical user interface.
    Type: Application
    Filed: November 16, 2018
    Publication date: March 21, 2019
    Inventors: Noha El-Zehiry, Shanhui Sun, Bogdan Georgescu, Lance Ladic, Ali Kamen
  • Publication number: 20190053858
    Abstract: An apparatus and method for tracking the position and orientation of one or more objects in three dimensional space is disclosed. One or more tracked sensor units are each connected with a respective object. Each tracked sensor unit includes one or more light sources and an inertial measurement unit. One or more position sensitive detector tracking devices track the position of the tracked sensor units. Each position sensitive detector tracking device includes a plurality of position sensitive detector sensors combined with optical lenses that focus light from a larger field of view onto each position sensitive detector sensor. The position and orientation of each object in three-dimensional space is calculated from the output of the inertial measurement unit of the respective tracked sensor unit and the output of the one or more position sensitive detector tracking devices in response to light emitted from the one or more light sources of the respective tracked sensor unit.
    Type: Application
    Filed: August 20, 2018
    Publication date: February 21, 2019
    Inventors: Ankur Kapoor, Ali Kamen, Gianluca Paladini