Patents by Inventor Daniela Seidel

Daniela Seidel 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: 11288805
    Abstract: A computer-implemented method and a data processing apparatus provide and apply a trained probabilistic graphical model for verifying and/or improving the consistency of labels within the scope of medical image processing. Also provided are a computer-implemented method for verifying and/or improving the consistency of labels within the scope of medical imaging processing, a data processing apparatus embodied to verify and/or improve the consistency of labels within the scope of medical image processing, and a corresponding computer program product and a computer-readable medium.
    Type: Grant
    Filed: April 1, 2020
    Date of Patent: March 29, 2022
    Assignee: Siemens Healthcare Diagnostics Inc.
    Inventors: Markus Michael Geipel, Florian Büttner, Gaby Marquardt, Daniela Seidel, Christoph Tietz
  • Publication number: 20220012531
    Abstract: The aim of the invention is to configure an image analysis device (BA). This is achieved in that a plurality of training images (TPIC) assigned to an object type (OT) and an object sub-type (OST) are fed into a first neural network module (CNN) in Order to detect image features. Furthermore, training output data sets (FEA) of the first neural network module (CNN) are fed into a second neural network module (MLP) in Order to detect object types using image features. According to the invention, the first and second neural network module (CNN, MLP) are trained together such that training output data sets (OOT) of the second neural network module (MLP) at least approximately reproduce the object types (OT) assigned to the training images (TPIC).
    Type: Application
    Filed: September 16, 2019
    Publication date: January 13, 2022
    Inventors: Markus Michael Geipel, Florian Büttner, Christoph Tietz, Gaby Marquardt, Daniela Seidel
  • Publication number: 20210239580
    Abstract: The invention relates to a method for fixing a thin-film material to a flat surface of a slide for a microscopy apparatus, by means of a liquid. The method comprises: applying a quantity of liquid to the flat surface of the slide; applying the thin-film material to the surface of the slide, which is wetted at least in part, preferably completely with liquid; applying a sample to be microscopically examined to the surface of the thin-film material which faces away from the surface of the slide wetted with liquid; wherein the surface of the thin-film material facing away from the surface of the slide wetted with liquid is hydrophilic.
    Type: Application
    Filed: August 26, 2019
    Publication date: August 5, 2021
    Inventors: Thomas Engel, Gabriele Hörnig, Gaby Marquardt, Daniela Seidel
  • Publication number: 20210201151
    Abstract: To train a machine learning routine (BNN), a sequence of first training data (PIC) is read in through the machine learning routine. The machine learning routine is trained using the first training data, wherein a plurality of learning parameters (LP) of the machine learning routine is set by the training. Furthermore, a value distribution (VLP) of the learning parameters, which occurs during the training, is determined and a continuation signal (CN) is generated on the basis of the determined value distribution of the learning parameters. Depending on the continuation signal, the training is then continued with a further sequence of the first training data or other training data (PIC2) are requested for the training.
    Type: Application
    Filed: July 29, 2019
    Publication date: July 1, 2021
    Inventors: Markus Michael Geipel, Stefan Depeweg, Christoph Tietz, Gaby Marquardt, Daniela Seidel
  • Patent number: 10801944
    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: Grant
    Filed: January 26, 2017
    Date of Patent: October 13, 2020
    Assignee: Siemens Healthcare GmbH
    Inventors: Noha Youssry El-Zehiry, Oliver Hayden, Ali Kamen, Lukas Richter, Manfred Stanzel, Matthias Ugele, Daniela Seidel, Gaby Marquardt, Oliver Schmidt
  • Publication number: 20200320709
    Abstract: The present invention relates to a computer-implemented method and a data processing apparatus for providing and applying a trained probabilistic graphical model for verifying and/or improving the consistency of labels within the scope of medical image processing, the use of the model for verifying and/or improving the consistency of labels within the scope of medical image processing, a computer-implemented method for verifying and/or improving the consistency of labels within the scope of medical imaging processing, a data processing apparatus embodied to verify and/or improve the consistency of labels within the scope of medical image processing, and a corresponding computer program product and a computer-readable medium.
    Type: Application
    Filed: April 1, 2020
    Publication date: October 8, 2020
    Inventors: Markus Michael Geipel, Florian Büttner, Gaby Marquardt, Daniela Seidel, Christoph Tietz
  • 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