Patents by Inventor Jens Wetzl

Jens Wetzl 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: 11911129
    Abstract: A trained deep learning network is for determining a cardiac phase in magnet resonance imaging. In an embodiment, the trained deep learning network includes an input layer; an output layer; and a number of hidden layers between input layer and output layer, the layers processing input data entered into the input layer. In an embodiment, the deep learning network is designed and trained to output a probability or some other label of a certain cardiac phase at a certain time from entered input data. A method for determining a cardiac phase in magnet resonance imaging; a related device; a training method for the deep learning network; a control device and a related magnetic resonance imaging system are also disclosed.
    Type: Grant
    Filed: March 4, 2021
    Date of Patent: February 27, 2024
    Assignee: Siemens Healthineers AG
    Inventors: Elisabeth Hoppe, Jens Wetzl, Seung Su Yoon
  • Publication number: 20240037815
    Abstract: Systems and methods for recreating images from undersampled MRI image data includes capturing undersampled MRI data and enhancing it with multiple cascading stages, each including a data consistency block in parallel to a convolutional neural network (CNN). The data consistency block adjusts each input image by a sensitivity map and performs hard replacement of acquired lines in k-space into the image. The CNN estimates a regularizer term that attempts to minimize a difference between a true image and the output of the data consistency block. At each stage, the output of CNN and data consistency block are added to create a set of output images that feed into the next stage.
    Type: Application
    Filed: July 26, 2022
    Publication date: February 1, 2024
    Inventors: Vahid Ghodrati, Chang Gao, Peng Hu, Xiaodong Zhong, Jens Wetzl, Jianing Pang
  • Publication number: 20230360215
    Abstract: A frequency offset is selected based on similarity measures of multiple MRI images obtained from frequency scout measurements associated with multiple frequency offsets from a reference frequency of a magnetization excitation pulse. The similarity measure for each respective MRI image of the multiple MRI images is determined based on a comparison between at least one reference image and the respective MRI image. The at least one reference image is determined from the multiple MRI images based on spectrum information of each of the multiple MRI images. Such methods facilitate automatically determining/selecting a more optimal frequency offset for an MRI scan following a frequency scout scan, in particular, for an SSFP or a bSSFP pulse sequence, and thereby banding artifacts and/or flow-related artifacts can be reduced for the MRI scan.
    Type: Application
    Filed: May 3, 2023
    Publication date: November 9, 2023
    Applicant: Siemens Healthcare GmbH
    Inventors: Seung Su YOON, Jens WETZL, Fasil GADJIMURADOV, Michaela SCHMIDT
  • Publication number: 20230252640
    Abstract: A computer-implemented method for determining scar segmentation includes receiving a medical image of an object to be segmented acquired after an application of a low-dose of contrast agent, wherein the low-dose of contrast agent comprises less contrast agent than a standard full-dose of contrast agent; and determining a scar segmentation mask by applying a trained artificial neural network to the medical image.
    Type: Application
    Filed: February 1, 2023
    Publication date: August 10, 2023
    Applicant: Siemens Healthcare GmbH
    Inventors: Marc VORNEHM, Daniel Giese, Jens Wetzl, Elisabeth Preuhs
  • Patent number: 11615529
    Abstract: Systems and methods for predicting a location for acquiring a target view of an anatomical object of interest in an input image are provided. An input image of an anatomical object of interest of a patient is received. An output image is generated using a machine learning based network. The output image depicts a projection of a 3D image plane for acquiring a target view of the anatomical object of interest identified on the input image. The output image is output.
    Type: Grant
    Filed: November 18, 2020
    Date of Patent: March 28, 2023
    Assignee: Siemens Healthcare GmbH
    Inventors: Teodora Chitiboi, Saikiran Rapaka, Puneet Sharma, Jens Wetzl, Christian Geppert, Michaela Schmidt
  • Publication number: 20230086229
    Abstract: A computer-implemented method for determining an orientation of at least one diagnostically relevant sectional plane for heart imaging in a three-dimensional magnetic resonance imaging image dataset, comprises: providing the three-dimensional image dataset; applying a trained function to the three-dimensional image dataset to determine a position of at least one landmark; determining the orientation of the at least one diagnostically relevant sectional plane as a function of at least one landmark; and providing the orientation of the at least one diagnostically relevant sectional plane.
    Type: Application
    Filed: September 20, 2022
    Publication date: March 23, 2023
    Applicant: Siemens Healthcare GmbH
    Inventors: Daniel GIESE, Jens WETZL, Michaela SCHMIDT
  • Publication number: 20220338829
    Abstract: The disclosure relates to techniques for determining a motion parameter of a heart. A subset of a sequence of cardiac MR images is applied as a first input to a first trained convolutional neural network configured to determine, as a first output, a probability distribution of at least 2 anatomical landmarks. The sequence of cardiac MR images is cropped and realigned based on the at least 2 anatomical landmarks to determine a reframed and aligned sequence of new cardiac MR images showing the same orientation of the heart. The reframed and aligned sequence of new cardiac MR images is applied to a second trained convolutional neural network configured to determine, as a second output, a further probability distribution of the at least 2 anatomical landmarks in each new MR image of the reframed and aligned sequence, the motion parameter of the heart is determined based on the second output.
    Type: Application
    Filed: April 25, 2022
    Publication date: October 27, 2022
    Applicant: Siemens Healthcare GmbH
    Inventors: Daniel Giese, Jens Wetzl, Maria Monzon, Carola Fischer, Seung Su Yoon
  • Patent number: 11455734
    Abstract: In a method for automatic motion detection in medical image-series, a dataset of a series of images is provided. The images can be of a similar region of interest that are recorded at consecutive points of time. The method can further include localizing a target in the images of the dataset and calculating a position of the target in the images to calculate localization data of the target, and calculating movement data of a movement of the target of temporal adjacent images of the images based on the localization data.
    Type: Grant
    Filed: April 17, 2020
    Date of Patent: September 27, 2022
    Assignee: Siemens Healthcare GmbH
    Inventors: Jens Wetzl, Seung Su Yoon, Christoph Forman, Michaela Schmidt, Elisabeth Hoppe
  • Publication number: 20220156918
    Abstract: Systems and methods for predicting a location for acquiring a target view of an anatomical object of interest in an input image are provided. An input image of an anatomical object of interest of a patient is received. An output image is generated using a machine learning based network. The output image depicts a projection of a 3D image plane for acquiring a target view of the anatomical object of interest identified on the input image. The output image is output.
    Type: Application
    Filed: November 18, 2020
    Publication date: May 19, 2022
    Inventors: Teodora Chitiboi, Saikiran Rapaka, Puneet Sharma, Jens Wetzl, Christian Geppert, Michaela Schmidt
  • Publication number: 20210287364
    Abstract: A trained deep learning network is for determining a cardiac phase in magnet resonance imaging. In an embodiment, the trained deep learning network includes an input layer; an output layer; and a number of hidden layers between input layer and output layer, the layers processing input data entered into the input layer. In an embodiment, the deep learning network is designed and trained to output a probability or some other label of a certain cardiac phase at a certain time from entered input data. A method for determining a cardiac phase in magnet resonance imaging; a related device; a training method for the deep learning network; a control device and a related magnetic resonance imaging system are also disclosed.
    Type: Application
    Filed: March 4, 2021
    Publication date: September 16, 2021
    Applicant: Siemens Healthcare GmbH
    Inventors: Elisabeth HOPPE, Jens WETZL, Seung Su YOON
  • Publication number: 20200334829
    Abstract: In a method for automatic motion detection in medical image-series, a dataset of a series of images is provided. The images can be of a similar region of interest that are recorded at consecutive points of time. The method can further include localizing a target in the images of the dataset and calculating a position of the target in the images to calculate localization data of the target, and calculating movement data of a movement of the target of temporal adjacent images of the images based on the localization data.
    Type: Application
    Filed: April 17, 2020
    Publication date: October 22, 2020
    Applicant: Siemens Healthcare GmbH
    Inventors: Jens Wetzl, Seung Su Yoon, Christoph Forman, Michaela Schmidt, Elisabeth Hoppe
  • Patent number: 10663546
    Abstract: In a method and magnetic resonance apparatus for recording diagnostic measurement data of a heart of an examination object, the magnetic resonance apparatus is operated by a control sequence wherein an RF pulse excites nuclear spins with a flip angle of at least 60°, the diagnostic measurement data are recorded in a coordinate system independent of the heart, and the basic magnetic field produced by the magnetic resonance apparatus is smaller than 1.0 tesla.
    Type: Grant
    Filed: January 26, 2018
    Date of Patent: May 26, 2020
    Assignee: Siemens Healthcare GmbH
    Inventors: Christoph Forman, Edgar Mueller, Michaela Schmidt, Jens Wetzl
  • Publication number: 20200103480
    Abstract: In a parameter value determination method, parameter values are determined based on at least two previously determined most similar comparison signal curves. As a result, the parameters for determining can be determined with a resolution greater than the resolution, underlying the comparison signal curves, of the values of the parameters to be determined. Advantageously, the determination of the parameter values are not limited to the values of the comparison signal curves, in other words, are not limited to the lattice/grid of the dictionary.
    Type: Application
    Filed: September 26, 2019
    Publication date: April 2, 2020
    Applicant: Siemens Healthcare GmbH
    Inventors: Mathias Nittka, Gregor Koerzdoerfer, Peter Speier, Jens Wetzl
  • Patent number: 10416257
    Abstract: A method for generating at least one acquisition template for an acquisition of magnetic resonance signals, an acquisition template generating unit, a magnetic resonance apparatus and a computer program product. At least one acquisition template is generated with an acquisition template generating unit. The at least one acquisition template has a plurality of spiral-like spokes in a k-space, each spoke having a plurality of spiral points.
    Type: Grant
    Filed: February 21, 2017
    Date of Patent: September 17, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Jens Wetzl, Christoph Forman, Peter Speier
  • Patent number: 10165960
    Abstract: In a method and apparatus for producing respiration-corrected MR images of an examination volume containing the heart of a patient during respiratory movement of MR signals are recorded continuously during multiple cardiac cycles, each cardiac cycle having multiple time segments. One 2D navigator image data record per cardiac cycle is recorded during a time segment of that cardiac cycle, with k-space being filled along a Cartesian trajectory such that a spatial resolution is achieved in two spatial directions of the examination volume. Also, multiple 3D image data records are recorded in the other time segments of that cardiac cycle, with Cartesian filling of raw data space such that a spatial resolution is achieved in all three spatial directions of the examination volume. The respiratory movement is then determined from these navigator data records. The determined respiratory movement is corrected in the recorded MR signals.
    Type: Grant
    Filed: March 26, 2018
    Date of Patent: January 1, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Christoph Forman, Ivo Prochaska, Jens Wetzl
  • Publication number: 20180271400
    Abstract: In a method and apparatus for producing respiration-corrected MR images of an examination volume containing the heart of a patient during respiratory movement of MR signals are recorded continuously during multiple cardiac cycles, each cardiac cycle having multiple time segments. One 2D navigator image data record per cardiac cycle is recorded during a time segment of that cardiac cycle, with k-space being filled along a Cartesian trajectory such that a spatial resolution is achieved in two spatial directions of the examination volume. Also, multiple 3D image data records are recorded in the other time segments of that cardiac cycle, with Cartesian filling of raw data space such that a spatial resolution is achieved in all three spatial directions of the examination volume. The respiratory movement is then determined from these navigator data records. The determined respiratory movement is corrected in the recorded MR signals.
    Type: Application
    Filed: March 26, 2018
    Publication date: September 27, 2018
    Applicant: Siemens Healthcare GmbH
    Inventors: Christoph Forman, Ivo Prochaska, Jens Wetzl
  • Publication number: 20180217215
    Abstract: In a method and magnetic resonance apparatus for recording diagnostic measurement data of a heart of an examination object, the magnetic resonance apparatus is operated by a control sequence wherein an RF pulse excites nuclear spins with a flip angle of at least 60°, the diagnostic measurement data are recorded in a coordinate system independent of the heart, and the basic magnetic field produced by the magnetic resonance apparatus is smaller than 1.0 tesla.
    Type: Application
    Filed: January 26, 2018
    Publication date: August 2, 2018
    Applicant: Siemens Healthcare GmbH
    Inventors: Christoph Forman, Edgar Mueller, Michaela Schmidt, Jens Wetzl
  • Patent number: 10001539
    Abstract: A method is for determining a type of reconstruction of image data from a magnetic resonance measurement of an examination object by way of a magnetic resonance device. In an embodiment, the method includes determining at least one first parameter which includes information about a breathing process of the examination object; comparing the at least one first parameter with at least one second parameter from a maintained database; and determining a type of reconstruction of image data of the magnetic resonance measurement according to the comparison that has been made. In an example embodiment, at least one of the at least one first parameter and the at least one second parameter is derived from a histogram of respiratory phases and the maintained database includes a self-learning system.
    Type: Grant
    Filed: August 4, 2015
    Date of Patent: June 19, 2018
    Assignee: SIEMENS AKTIENGESELLSCHAFT
    Inventors: Christoph Forman, Jens Wetzl
  • Publication number: 20170242086
    Abstract: A method for generating at least one acquisition template for an acquisition of magnetic resonance signals, an acquisition template generating unit, a magnetic resonance apparatus and a computer program product. At least one acquisition template is generated with an acquisition template generating unit. The at least one acquisition template has a plurality of spiral-like spokes in a k-space, each spoke having a plurality of spiral points.
    Type: Application
    Filed: February 21, 2017
    Publication date: August 24, 2017
    Inventors: Jens Wetzl, Christoph Forman, Peter Speier
  • Publication number: 20160054419
    Abstract: A method is disclosed for determining a type of reconstruction of image data from a magnetic resonance measurement of an examination object by way of a magnetic resonance device. In an embodiment, the method includes determining at least one first parameter which includes information about a breathing process of the examination object; comparing the at least one first parameter with at least one second parameter from a maintained database; and determining a type of reconstruction of image data of the magnetic resonance measurement according to the comparison that has been made. In an example embodiment, at least one of the at least one first parameter and the at least one second parameter is derived from a histogram of respiratory phases and the maintained database includes a self-learning system.
    Type: Application
    Filed: August 4, 2015
    Publication date: February 25, 2016
    Inventors: Christoph FORMAN, Jens WETZL