Patents by Inventor Dime Vitanovski
Dime Vitanovski 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).
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Patent number: 9196049Abstract: A system and method for regression-based segmentation of the mitral valve in 2D+t cardiac magnetic resonance (CMR) slices is disclosed. The 2D+t CMR slices are acquired according to a mitral valve-specific acquisition protocol introduced herein. A set of mitral valve landmarks is detected in each 2D CMR slice and mitral valve contours are estimated in each 2D CMR slice based on the detected landmarks. A full mitral valve model is reconstructed from the mitral valve contours estimated in the 2D CMR slices using a trained regression model. Each 2D CMR slice may be a cine image acquired over a full cardiac cycle. In this case, the segmentation method reconstructs a patient-specific 4D dynamic mitral valve model from the 2D+t CMR image data.Type: GrantFiled: March 9, 2012Date of Patent: November 24, 2015Assignee: Siemens AktiengesellschaftInventors: Razvan Ioan Ionasec, Dime Vitanovski, Alexey Tsymbal, Gareth Funka-Lea, Dorin Comaniciu, Andreas Greiser, Edgar Mueller
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Patent number: 9135699Abstract: A method and system for non-invasive hemodynamic assessment of aortic coarctation from medical image data, such as magnetic resonance imaging (MRI) data is disclosed. Patient-specific lumen anatomy of the aorta and supra-aortic arteries is estimated from medical image data of a patient, such as contrast enhanced MRI. Patient-specific aortic blood flow rates are estimated from the medical image data of the patient, such as velocity encoded phase-contrasted MRI cine images. Patient-specific inlet and outlet boundary conditions for a computational model of aortic blood flow are calculated based on the patient-specific lumen anatomy, the patient-specific aortic blood flow rates, and non-invasive clinical measurements of the patient. Aortic blood flow and pressure are computed over the patient-specific lumen anatomy using the computational model of aortic blood flow and the patient-specific inlet and outlet boundary conditions.Type: GrantFiled: March 14, 2013Date of Patent: September 15, 2015Assignee: Siemens AktiengesellschaftInventors: Kristof Ralovich, Lucian Mihai Itu, Viorel Mihalef, Puneet Sharma, Razvan Ioan Ionasec, Dime Vitanovski, Waldemar Krawtschuk, Dorin Comaniciu
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Patent number: 9033887Abstract: 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.Type: GrantFiled: May 30, 2013Date of Patent: May 19, 2015Assignees: Siemens Corporation, Siemens Medical Solutions USA, Inc., Siemens AktiengesellschaftInventors: Razvan Ioan Ionasec, Dime Vitanovski, Yang Wang, Bogdan Georgescu, Ingmar Voigt, Saurabh Datta, Dorin Comaniciu
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Patent number: 8812431Abstract: 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.Type: GrantFiled: January 28, 2011Date of Patent: August 19, 2014Assignee: Siemens AktiengesellschaftInventors: Ingmar Voigt, Dime Vitanovski, Razvan Ioan Ionasec, Alexey Tsymbal, Bogdan Georgescu, Shaohua Kevin Zhou, Martin Huber, Dorin Comaniciu
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Patent number: 8682626Abstract: 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.Type: GrantFiled: April 20, 2011Date of Patent: March 25, 2014Assignee: Siemens AktiengesellschaftInventors: Razvan Ioan Ionasec, Ingmar Voigt, Viorel Mihalef, Sasa Grbic, Dime Vitanovski, Yang Wang, Yefeng Zheng, Bogdan Georgescu, Dorin Comaniciu, Puneet Sharma, Tommaso Mansi
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Publication number: 20140052001Abstract: 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.Type: ApplicationFiled: May 30, 2013Publication date: February 20, 2014Inventors: Razvan Ioan Ionasec, Dime Vitanovski, Yang Wang, Bogdan Georgescu, Ingmar Voigt, Saurabh Datta, Dorin Comaniciu
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Publication number: 20130243294Abstract: A method and system for non-invasive hemodynamic assessment of aortic coarctation from medical image data, such as magnetic resonance imaging (MRI) data is disclosed. Patient-specific lumen anatomy of the aorta and supra-aortic arteries is estimated from medical image data of a patient, such as contrast enhanced MRI. Patient-specific aortic blood flow rates are estimated from the medical image data of the patient, such as velocity encoded phase-contrasted MRI cine images. Patient-specific inlet and outlet boundary conditions for a computational model of aortic blood flow are calculated based on the patient-specific lumen anatomy, the patient-specific aortic blood flow rates, and non-invasive clinical measurements of the patient. Aortic blood flow and pressure are computed over the patient-specific lumen anatomy using the computational model of aortic blood flow and the patient-specific inlet and outlet boundary conditions.Type: ApplicationFiled: March 14, 2013Publication date: September 19, 2013Applicants: Siemens Aktiengesellschaft, Siemens CorporationInventors: Kristof Ralovich, Lucian Mihai Itu, Viorel Mihalef, Puneet Sharma, Razvan Ioan Ionasec, Dime Vitanovski, Waldemar Krawtschuk, Dorin Comaniciu
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Patent number: 8538109Abstract: 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.Type: GrantFiled: March 16, 2010Date of Patent: September 17, 2013Assignee: Siemens AktiengesellschaftInventors: Dime Vitanovski, Razvan Ioan Ionasec, Bogdan Georgescu, Martin Huber, Dorin Comaniciu
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Publication number: 20120232379Abstract: A system and method for regression-based segmentation of the mitral valve in 2D+t cardiac magnetic resonance (CMR) slices is disclosed. The 2D+t CMR slices are acquired according to a mitral valve-specific acquisition protocol introduced herein. A set of mitral valve landmarks is detected in each 2D CMR slice and mitral valve contours are estimated in each 2D CMR slice based on the detected landmarks. A full mitral valve model is reconstructed from the mitral valve contours estimated in the 2D CMR slices using a trained regression model. Each 2D CMR slice may be a cine image acquired over a full cardiac cycle. In this case, the segmentation method reconstructs a patient-specific 4D dynamic mitral valve model from the 2D+t CMR image data.Type: ApplicationFiled: March 9, 2012Publication date: September 13, 2012Applicant: Siemens CorporationInventors: Razvan Ioan Ionasec, Dime Vitanovski, Alexey Tsymbal, Gareth Funka-Lea, Dorin Comaniciu, Andreas Greiser, Edgar Mueller
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Patent number: 8218845Abstract: 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.Type: GrantFiled: December 1, 2008Date of Patent: July 10, 2012Assignee: Siemens AktiengesellschaftInventors: Michael Lynch, Razvan Ionasec, Bogdan Georgescu, Dorin Comaniciu, Dime Vitanovski
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Publication number: 20120022843Abstract: 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.Type: ApplicationFiled: April 20, 2011Publication date: January 26, 2012Inventors: Razvan Ioan Ionasec, Ingmar Voigt, Viorel Mihalef, Sasa Grbic, Dime Vitanovski, Yang Wang, Yefeng Zheng, Bogdan Georgescu, Dorin Comaniciu, Puneet Sharma, Tommaso Mansi
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Publication number: 20110191283Abstract: 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.Type: ApplicationFiled: January 28, 2011Publication date: August 4, 2011Applicants: Siemens Corporation, Siemens AktiengesellschaftInventors: Ingmar Voigt, Dime Vitanovski, Razvan Ioan Ionasec, Alexey Tsymbal, Bogdan Georgescu, Shaohua Kevin Zhou, Martin Huber, Dorin Comaniciu
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Publication number: 20100239147Abstract: 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.Type: ApplicationFiled: March 16, 2010Publication date: September 23, 2010Applicants: Siemens Corporation, Siemens AktiengesellschaftInventors: Dime Vitanovski, Razvan Ioan Ionasec, Bogdan Georgescu, Martin Huber, Dorin Comaniciu
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Publication number: 20090154785Abstract: 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.Type: ApplicationFiled: December 1, 2008Publication date: June 18, 2009Inventors: Michael Lynch, Razvan Ionasec, Bogdan Georgescu, Dorin Comaniciu, Dime Vitanovski