Patents by Inventor Burak Acar
Burak Acar 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: 11937139Abstract: Methods, systems, and apparatus' for optimizing network performance are described herein. A Cloud-Server may optimize one or more mesh networks of a plurality of 802.11 access points (APs) and stations (STA) connected to the APs. The Cloud-Server may work with a client steering daemon (CSD) miming on each AP. The Cloud-Server may operate in a location that is remote to the AP(s). The Cloud-Server may collect, store, and process network and client related data from one or more CSDs. The processing may include measuring network (e.g., premises) and client (e.g., STA) performance as well as analyzing (e.g., machine learning, etc.) to determine network parameters that will optimize network performance The Cloud-Server may then apply these network parameters to the relevant CSDs in order to improve per client and per network performance.Type: GrantFiled: October 22, 2019Date of Patent: March 19, 2024Assignee: AIRTIES S.A.S.Inventors: Irfan Acar, Metin Ismail Taskin, Raph Weyman, Burak Onat
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Patent number: 7729739Abstract: A method for detecting and identifying structures of interest such as colonic polyps or similar structures like lung nodules in volumetric (medical) images data is provided. The method includes obtaining a heat diffusion field (HDF) by applying a heat diffusion scheme to a volume of interest that includes structures. The obtained heat diffusion field is then used for identifying a structure of interest from the structures in the volume of interest using a geometrical analysis of the heat diffusion field. The heat diffusion scheme is, at least partly, governed by non-linear diffusion parameters. The identification includes two parts: (i) the computation of a spherical symmetry parameter, and (ii) the performance of a local analysis of the volume of interest and computation of a triangulization parameter.Type: GrantFiled: November 29, 2004Date of Patent: June 1, 2010Assignee: The Board of Trustees of the Leland Stanford Junior UniversityInventors: Burak Acar, Ender Konukoglu, Christopher F. Beaulieu, Sandy A. Napel, David S. Paik
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Patent number: 7272251Abstract: A method to detect and classify a structure of interest in a medical image is provided to enable high specificity without sacrificing the sensitivity of detection. The method is based on representing changes in three-dimensional image data with a vector field, characterizing the topology of this vector field and using the characterized topology of the vector field for classification of a structure of interest. The method could be used as a stand-alone method or as a post-processing method to enhance and classify outputs of a high-sensitivity low-specificity method to eliminate false positives.Type: GrantFiled: September 30, 2003Date of Patent: September 18, 2007Assignee: The Board of Trustees of the Leland Stanford Junior UniversityInventors: Burak Acar, Christopher F. Beaulieu, Salih B. Gokturk, Carlo Tomasi, David S. Paik, R. Brooke Jeffrey, Jr., Sandy A. Napel
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Patent number: 7224827Abstract: An automatic method for the registration of prone and supine computed tomographic colonography data is provided. The method improves the radiologist's overall interpretation efficiency as well as provides a basis for combining supine/prone computer-aided detection results automatically. The method includes determining (centralized) paths or axes of the colon from which relatively stationary points of the colon are matched for both supine and prone positions. Stretching and/or shrinking of either the supine or prone path perform registration of these points. The matching and registration occurs in an iterative and recursive manner and is considered finished based on one or more decision criteria.Type: GrantFiled: September 26, 2003Date of Patent: May 29, 2007Assignee: The Board of Trustees of the Leland Stanford Junior UniversityInventors: Burak Acar, Christopher F. Beaulieu, David S. Paik, Sandy A. Napel, R. Brooke Jeffrey
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Patent number: 6969991Abstract: A general mathematical framework is formulated to characterize the contribution of gradient non-uniformities to diffusion tensor imaging in MRI. Based on a model expansion, the actual gradient field is approximated and employed, after elimination of geometric distortions, for predicting and correcting the errors in diffusion encoding. Prior to corrections, experiments clearly reveal marked deviations of the calculated diffusivity for fields of view generally used in diffusion experiments. These deviations are most significant with greater distance from the magnet's isocenter. For a FOV of 25 cm the resultant errors in absolute diffusivity can range from approximately ?10 to +20 percent. Within the same field of view, the diffusion-encoding direction and the orientation of the calculated eigenvectors can be significantly altered if the perturbations by the gradient non-uniformities are not considered. With the proposed correction scheme most of the errors introduced by gradient non-uniformities can be removed.Type: GrantFiled: December 11, 2002Date of Patent: November 29, 2005Assignee: The Board of Trustees of the Leland Stanford Junior UniversityInventors: Roland Bammer, Michael Markl, Burak Acar, Norbert J. Pelc, Michael E. Moseley
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Publication number: 20050149286Abstract: A method for detecting and identifying structures of interest such as colonic polyps or similar structures like lung nodules in volumetric (medical) images data is provided. The method includes obtaining a heat diffusion field (HDF) by applying a heat diffusion scheme to a volume of interest that includes structures. The obtained heat diffusion field is then used for identifying a structure of interest from the structures in the volume of interest using a geometrical analysis of the heat diffusion field. The heat diffusion scheme is, at least partly, governed by non-linear diffusion parameters. The identification includes two parts: (i) the computation of a spherical symmetry parameter, and (ii) the performance of a local analysis of the volume of interest and computation of a triangulization parameter.Type: ApplicationFiled: November 29, 2004Publication date: July 7, 2005Inventors: Burak Acar, Ender Konukoglu, Christopher Beaulieu, Sandy Napel, David Paik
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Publication number: 20040141638Abstract: A method to detect and classify a structure of interest in a medical image is provided to enable high specificity without sacrificing the sensitivity of detection. The method is based on representing changes in three-dimensional image data with a vector field, characterizing the topology of this vector field and using the characterized topology of the vector field for classification of a structure of interest. The method could be used as a stand-alone method or as a post-processing method to enhance and classify outputs of a high-sensitivity low-specificity method to eliminate false positives.Type: ApplicationFiled: September 30, 2003Publication date: July 22, 2004Inventors: Burak Acar, Christopher F. Beaulieu, Salih B. Gokturk, Carlo Tomasi, David S. Paik, R. Brooke Jeffrey, Sandy A. Napel
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Publication number: 20040136584Abstract: An automatic method for the registration of prone and supine computed tomographic colonography data is provided. The method improves the radiologist's overall interpretation efficiency as well as provides a basis for combining supine/prone computer-aided detection results automatically. The method includes determining (centralized) paths or axes of the colon from which relatively stationary points of the colon are matched for both supine and prone positions. Stretching and/or shrinking of either the supine or prone path perform registration of these points. The matching and registration occurs in an iterative and recursive manner and is considered finished based on one or more decision criteria.Type: ApplicationFiled: September 26, 2003Publication date: July 15, 2004Inventors: Burak Acar, Christopher F. Beaulieu, David S. Paik, Sandy A. Napel, R. Brooke Jeffrey
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Publication number: 20040113615Abstract: A general mathematical framework is formulated to characterize the contribution of gradient non-uniformities to diffusion tensor imaging in MRI. Based on a model expansion, the actual gradient field is approximated and employed, after elimination of geometric distortions, for predicting and correcting the errors in diffusion encoding. Prior to corrections, experiments clearly reveal marked deviations of the calculated diffusivity for fields of view generally used in diffusion experiments. These deviations are most significant with greater distance from the magnet's isocenter. For a FOV of 25 cm the resultant errors in absolute diffusivity can range from approximately −10 to +20 percent. Within the same field of view, the difflision-encoding direction and the orientation of the calculated eigenvectors can be significantly altered if the perturbations by the gradient non-uniformities are not considered.Type: ApplicationFiled: December 11, 2002Publication date: June 17, 2004Applicant: THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITYInventors: Roland Bammer, Michael Markl, Burak Acar, Norbert J. Pelc, Michael E. Moseley
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Patent number: 6438409Abstract: New methods of characterising ventricular operations by measuring propagation characterisics of the repolarisation wavefront (the T wave) are disclosed, the methods use new descriptions of T wave Morphology Dispersion (TMD), Total Cosin R_ to _T (TCRT) and T wave energy residium to quantify the wavefront characteristics, these descriptors measure the spatial variability of the T wave Morphology, the vector deviations between the depolarisation and repolarisation wavefronts and the energy of the non-dipolar components of the ECG vector respectively. TCRT also provides a responsive descriptor for measuring autonomic tone. As such, has applications for improved pacing and autonomic nervous system monitors.Type: GrantFiled: March 24, 2000Date of Patent: August 20, 2002Assignee: Medtronic, Inc.Inventors: Marek Malik, Burak Acar, Velislav Nikolaev Batchvarov