Patents by Inventor Frederick Klauschen

Frederick Klauschen 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).

  • Method and system for the automatic analysis of an image of a biological sample
    Patent number: 9558550
    Abstract: Method for the automatic analysis of an image of a biological sample with respect to a pathological relevance, wherein a)local features of the image are aggregated to a global feature of the image using a bag of visual word approach, b) step a) is repeated at least two times using different methods resulting in at least two bag of word feature datasets, c) computation of at least two similarity measures using the bag of word features obtained from a training image dataset and bag of word features from the image, d) the image training dataset comprising a set of visual words, classifier parameters, including kernel weights and bag of word features from the training images, e) the computation of the at least two similarity measures is subject to an adaptive computation of kernel normalization parameters and/or kernel width parameters, f) for each image one score is computed depending on the classifier parameters and kernel weights and the at least two similarity measures, the at least one score being a measure
    Type: Grant
    Filed: September 14, 2012
    Date of Patent: January 31, 2017
    Assignees: Technische Universität Berlin, Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V.
    Inventors: Frederick Klauschen, Motoaki Kawanabe, Klaus-Robert Mueller, Alexander Binder
  • Method and System for the Automatic Analysis of an Image of a Biological Sample
    Publication number: 20150003701
    Abstract: Method for the automatic analysis of an image (1, 11, 12, 13) of a biological sample with respect to a pathological relevance, wherein fj local features of the image (1, 11, 12, 13) are aggregated to a global feature of the image (1, 11, 12, 13) using a bag of visual word approach, g) step a) is repeated at least two times using different methods resulting in at least two bag of word feature datasets, h) computation of at least two similarity measures using the bag of word features obtained from a training image dataset and bag of word features from the image (1, 11, 12, 13) i) the image training dataset comprising a set of visual words, classifier parameters, including kernel weights and bag of word features from the training images, j) the computation of the at least two similarity measures is subject: to an adaptive computation of kernel normalization parameters and/or kernel width parameters, f) for each image (1, 11, 12, 13) one score is computed depending on the classifier parameters and kernel weights
    Type: Application
    Filed: September 14, 2012
    Publication date: January 1, 2015
    Applicants: TECHNISCHE UNIVERSITAT BERLIN, Fraunhofer-Gesellschaft zur Foerderung der angewandten Forschung e.V.
    Inventors: Frederick Klauschen, Motoaki Kawanabe, Klaus-Robert Mueller, Alexander Binder