Patents by Inventor Mehmet Akif Gulsun

Mehmet Akif Gulsun 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).

  • Publication number: 20250111656
    Abstract: Systems and methods for performing a medical analysis task using a trained machine learning based task network are provided. Input medical data is received. A medical analysis task is performed using a trained machine learning based task network based on the input medical data. Results of the medical analysis task are output. The trained machine learning based task network is trained by: receiving unannotated training medical data; generating weakly-supervised labels for the unannotated training medical data using one or more trained machine learning based supervised learning networks; training the machine learning based task network for performing the medical analysis task based on 1) the unannotated training medical data, 2) self-supervised labels for the unannotated training medical data learned via self-supervised learning, and 3) the generated weakly-supervised labels for the unannotated training medical data; and outputting the trained machine learning based task network.
    Type: Application
    Filed: September 28, 2023
    Publication date: April 3, 2025
    Inventors: Venkatesh Narasimha Murthy, Bogdan Georgescu, Florin-Cristian Ghesu, Mehmet Akif Gulsun, Dominik Neumann, Alexandru Constantin Serban, Dorin Comaniciu
  • Publication number: 20250099060
    Abstract: Techniques for processing multiple cardiac images are disclosed. The multiple cardiac images, each of which depicts a portion of coronary arteries, i.e., the same portion of coronary arteries, within an anatomical region of interest, are obtained either during or after an angiography exam. A respective set of lumen radius measurements is determined based on each of the multiple cardiac images and comprises multiple lumen radius measurements respectively associated with multiple locations of the portion of the coronary arteries. A maximum stenosis severity profile and a minimum stenosis severity profile associated with the portion of the coronary arteries are respectively determined based on the respective sets of lumen radius measurements. A lumen radius profile associated with the portion of the coronary arteries is determined based on the maximum stenosis severity profile and the minimum stenosis severity profile.
    Type: Application
    Filed: August 27, 2024
    Publication date: March 27, 2025
    Inventors: Alexandru Turcea, Serkan Cimen, Dominik Neumann, Martin Berger, Mehmet Akif Gulsun, Lucian Mihai Itu, Puneet Sharma
  • Publication number: 20250014174
    Abstract: Systems and methods for training a machine learning based network based on PCCT (photon counting computed tomography) imaging data. PCCT imaging data acquired from a PCCT imaging device is received. One or more PCCT virtual images are generated from the PCCT imaging data. A machine learning based network is trained for performing a medical imaging analysis task based on the one or more PCCT virtual images. The trained machine learning based network is output.
    Type: Application
    Filed: July 3, 2023
    Publication date: January 9, 2025
    Inventors: Mehmet Akif Gulsun, Puneet Sharma, Max Schöbinger
  • Publication number: 20250009314
    Abstract: Systems and methods for performing a medical imaging analysis task from PCCT (photon counting computed tomography) imaging data are provided. PCCT imaging data acquired from a PCCT imaging device is received. A plurality of PCCT virtual images is generated from the PCCT imaging data. A plurality of medical imaging analysis sub-tasks is performed based on the plurality of PCCT virtual images using a plurality of machine learning based networks. Results of the medical imaging analysis sub-tasks are combined to generate results of a medical imaging analysis task. The results of the medical imaging analysis task are output.
    Type: Application
    Filed: July 3, 2023
    Publication date: January 9, 2025
    Inventors: Mehmet Akif Gulsun, Puneet Sharma, Max Schöbinger
  • Publication number: 20240321432
    Abstract: At least one example embodiment provides a computer-implemented method for evaluating at least one image data set of an imaging region of a patient, wherein at least one evaluation information describing at least one medical condition in an anatomical structure of the imaging region is determined.
    Type: Application
    Filed: June 5, 2024
    Publication date: September 26, 2024
    Applicant: Siemens Healthineers AG
    Inventors: Max SCHOEBINGER, Michael WELS, Chris SCHWEMMER, Mehmet Akif GULSUN, Serkan CIMEN, Felix LADES, Christian HOPFGARTNER, Suha AYMAN, Rumman KHAN, Ashish JAISWAL
  • Patent number: 12100502
    Abstract: Systems and methods for determining corresponding locations of points of interest in a plurality of input medical images are provided. A plurality of input medical images comprising a first input medical image and one or more additional input medical images is received. The first input medical image identifies a location of a point of interest. A set of features is extracted from each of the plurality of input medical images. Features between each of the sets of features are related using a machine learning based relational network. A location of the point of interest in each of the one or more additional input medical images that corresponds to the location of the point of interest in the first input medical image is identified based on the related features. The location of the point of interest in each of the one or more additional input medical images is output.
    Type: Grant
    Filed: March 16, 2022
    Date of Patent: September 24, 2024
    Assignee: Siemens Healthineers AG
    Inventors: Serkan Cimen, Mehmet Akif Gulsun, Puneet Sharma
  • Patent number: 12094112
    Abstract: Systems and methods for automated assessment of a vessel are provided. One or more input medical images of a vessel of a patient are received. A plurality of vessel assessment tasks for assessing the vessel is performed using a machine learning based model trained using multi-task learning. The plurality of vessel assessment tasks comprises segmentation of reference walls of the vessel from the one or more input medical images and segmentation of lumen of the vessel from the one or more input medical images. Results of the plurality of vessel assessment tasks are output.
    Type: Grant
    Filed: January 27, 2022
    Date of Patent: September 17, 2024
    Assignee: Siemens Healthineers AG
    Inventors: Mehmet Akif Gulsun, Puneet Sharma, Diana Ioana Stoian, Max Schöbinger
  • Publication number: 20240260917
    Abstract: A vessel imaging sequence including plurality of vessel imaging frames and a corresponding ECG signal are generated by encoding, using a first encoder, an input vessel imaging sequence to generate a plurality of vessel latent space vectors, each vessel latent space vector corresponding to an input vessel imaging frame of the input vessel imaging sequence, encoding, using a second encoder, an input ECG signal to generate a plurality of ECG latent space vectors, decoding, using a first decoder, the plurality of vessel latent space vectors and the plurality of ECG latent space vectors to generate the vessel imaging sequence and decoding, using a second decoder, the vessel latent space vector and the ECG latent space vector to generate the ECG signal.
    Type: Application
    Filed: December 11, 2023
    Publication date: August 8, 2024
    Inventors: Venkatesh Narasimha Murthy, Anamaria Vizitiu, Mehmet Akif Gulsun, Sebastien Piat, Florin-Cristian Ghesu
  • Publication number: 20240215937
    Abstract: Techniques for processing multiple cardiac images are disclosed. The processing may take place either during or after an angiography exam of a coronary artery of interest. The multiple cardiac images are obtained either during or after the angiography exam. Each of the multiple cardiac images depicts a respective segment of the coronary artery of interest. A geometric structure of the coronary artery of interest is determined based on the multiple cardiac images. A lumped parameter model of the coronary artery of interest is determined based on the geometric structure, and respective values of at least one hemodynamic index at a position of the coronary artery of interest is determined based on the lumped parameter model of the coronary artery of interest.
    Type: Application
    Filed: November 8, 2023
    Publication date: July 4, 2024
    Inventors: Lucian Mihai Itu, Serkan Cimen, Martin Berger, Dominik Neumann, Alexandru Turcea, Mehmet Akif Gulsun, Tiziano Passerini, Puneet Sharma
  • Patent number: 12027253
    Abstract: At least one example embodiment provides a computer-implemented method for evaluating at least one image data set of an imaging region of a patient, wherein at least one evaluation information describing at least one medical condition in an anatomical structure of the imaging region is determined.
    Type: Grant
    Filed: April 27, 2022
    Date of Patent: July 2, 2024
    Assignee: SIEMENS HEALTHINEERS AG
    Inventors: Max Schoebinger, Michael Wels, Chris Schwemmer, Mehmet Akif Gulsun, Serkan Cimen, Felix Lades, Christian Hopfgartner, Suha Ayman, Rumman Khan, Ashish Jaiswal
  • Patent number: 11995834
    Abstract: One or more example embodiments of the present invention relates to a method for the automated determination of examination results in an image sequence from multiple chronologically consecutive frames, the method comprising determining diagnostic candidates in the form of contiguous image regions in the individual frames for a predefined diagnostic finding; and for a number of the diagnostic candidates, determining which candidate image regions in other frames correspond to the particular diagnostic candidate, determining whether the candidate image regions of the particular diagnostic candidate in the other frames overlap with other diagnostic candidates, generating a graph containing the determined diagnostic candidates of the frames as nodes and the determined overlaps as edges, and generating communities from nodes connected via edges.
    Type: Grant
    Filed: February 7, 2023
    Date of Patent: May 28, 2024
    Assignee: SIEMENS HEALTHINEERS AG
    Inventors: Dominik Neumann, Mehmet Akif Gulsun, Tiziano Passerini
  • Publication number: 20240161285
    Abstract: Various aspects of the disclosure generally pertain to determining estimates of hemodynamic properties based on angiographic x-ray examinations of a coronary system. Various aspects of the disclosure specifically pertain to determining such estimates based on single frame metrics operating on two-dimensional images. For example, the fractional flow reserve (FFR) can be computed.
    Type: Application
    Filed: September 12, 2023
    Publication date: May 16, 2024
    Inventors: Dominik Neumann, Alexandru Turcea, Lucian Mihai Itu, Tiziano Passerini, Mehmet Akif Gulsun, Martin Berger
  • Publication number: 20240104719
    Abstract: Systems and methods for automatic assessment of a vessel are provided. A temporal sequence of medical images of a vessel of a patient is received. A plurality of sets of output embeddings is generated using a machine learning based model trained using multi-task learning. The plurality of sets of output embeddings is generated based on shared features extracted from the temporal sequence of medical images. A plurality of vessel assessment tasks is performed by modelling each of the plurality of sets of output embeddings in a respective probabilistic distribution. Results of the plurality of vessel assessment tasks are output.
    Type: Application
    Filed: September 22, 2022
    Publication date: March 28, 2024
    Inventors: Mehmet Akif Gulsun, Diana Ioana Stoian, Vivek Singh, Puneet Sharma, Martin Berger
  • Publication number: 20240104796
    Abstract: System and methods for determining and implementing optimized reconstruction parameters for computer-aided diagnosis applications. A simulator generates image data using different combinations of reconstruction parameters. The image data is used to evaluate or train machine learned networks that are configured for computer-aided diagnosis applications to determine which reconstruction parameters are optimal for application or training.
    Type: Application
    Filed: September 27, 2022
    Publication date: March 28, 2024
    Inventors: Matthew Holbrook, Mehmet Akif Gulsun, Mariappan S. Nadar, Puneet Sharma, Boris Mailhe
  • Publication number: 20240046465
    Abstract: Angiography angles are determined. Patient information and target vessel information are obtained, wherein the patient information defines individual medical information of a patient and wherein the target vessel information defines at least one target vessel to be imaged. At least one angiography angle is determined based on the patient information and the target vessel information. Angiograms obtained using the at least one angiography angle are analyzed to determine a vessel coverage of the target vessel and based on the vessel coverage determines additional angiography angles.
    Type: Application
    Filed: June 27, 2023
    Publication date: February 8, 2024
    Inventors: Puneet Sharma, Mehmet Akif Gulsun, Tiziano Passerini, Serkan Cimen, Dominik Neumann, Martin Berger, Martin von Roden
  • Publication number: 20240029868
    Abstract: Systems and methods for performing a medical imaging analysis task are provided. One or more input medical images of a patient are received. The one or more input medical images are encoded into embeddings using a machine learning based encoder network. A medical imaging analysis task is performed based on the embeddings. Results of the medical imaging analysis task are output.
    Type: Application
    Filed: May 2, 2023
    Publication date: January 25, 2024
    Inventors: Mehmet Akif Gulsun, Vivek Singh, Diana Ioana Stoian, Alexandru Constantin Serban, Puneet Sharma, Venkatesh Narasimha Murthy
  • Patent number: 11861764
    Abstract: Systems and methods are provided for three dimensional depth reconstruction of vessels in two dimensional medical images. A medical image comprising braches of one or more vessels is received. A branch overlap image channel that represents a pixelwise probability that the branches overlap is generated. A set of branch orientation image channels are generated. Each branch orientation image channel is associated with one of a plurality of orientations. Each branch orientation image channel representing a image channel represents a pixelwise probability that the branches are oriented in its associated orientation. A multi-channel depth image is generated based on the branch overlap image channel and the set of branch orientation image channels. Each channel of the multi-channel depth image comprises portions of the branches corresponding to a respective depth.
    Type: Grant
    Filed: June 13, 2019
    Date of Patent: January 2, 2024
    Assignee: Siemens Healthcare GmbH
    Inventors: Thibaut Barroyer, Mehmet Akif Gulsun
  • Publication number: 20230298736
    Abstract: Systems and methods for determining corresponding locations of points of interest in a plurality of input medical images are provided. A plurality of input medical images comprising a first input medical image and one or more additional input medical images is received. The first input medical image identifies a location of a point of interest. A set of features is extracted from each of the plurality of input medical images. Features between each of the sets of features are related using a machine learning based relational network. A location of the point of interest in each of the one or more additional input medical images that corresponds to the location of the point of interest in the first input medical image is identified based on the related features. The location of the point of interest in each of the one or more additional input medical images is output.
    Type: Application
    Filed: March 16, 2022
    Publication date: September 21, 2023
    Inventors: Serkan Cimen, Mehmet Akif Gulsun, Puneet Sharma
  • Publication number: 20230289973
    Abstract: Various examples of the disclosure pertain to determining a label set for an anatomical structure such as a complex blood vessel, e.g., the coronary artery. The determining of the label set takes into account multiple inputs, such as the rule set of anatomical relationship between sub structures of the anatomical structure and a list of candidate labels and associated probabilities obtained for each one of the anatomical substructures.
    Type: Application
    Filed: March 9, 2023
    Publication date: September 14, 2023
    Applicant: Siemens Healthcare GmbH
    Inventors: Martin KRAUS, Mehmet Akif Gulsun
  • Publication number: 20230252636
    Abstract: One or more example embodiments of the present invention relates to a method for the automated determination of examination results in an image sequence from multiple chronologically consecutive frames, the method comprising determining diagnostic candidates in the form of contiguous image regions in the individual frames for a predefined diagnostic finding; and for a number of the diagnostic candidates, determining which candidate image regions in other frames correspond to the particular diagnostic candidate, determining whether the candidate image regions of the particular diagnostic candidate in the other frames overlap with other diagnostic candidates, generating a graph containing the determined diagnostic candidates of the frames as nodes and the determined overlaps as edges, and generating communities from nodes connected via edges.
    Type: Application
    Filed: February 7, 2023
    Publication date: August 10, 2023
    Applicant: Siemens Healthcare GmbH
    Inventors: Dominik NEUMANN, Mehmet Akif Gulsun, Tiziano Passerini