Patents by Inventor Edvin FORSGREN

Edvin FORSGREN 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: 11422355
    Abstract: A method is disclosed for acquiring a single, in-focus two-dimensional projection image of a live, three-dimensional cell culture sample, with a fluorescence microscope. One or more long-exposure “Z-sweep” images are obtained, i.e. via a single or series of continuous acquisitions, while moving the Z-focal plane of a camera through the sample, to produce one or more two-dimensional images of fluorescence intensity integrated over the Z-dimension. The acquisition method is much faster than a Z-stack method, which enables higher throughput and reduces the risk of exposing the sample to too much fluorescent light. The long-exposure Z-sweep image(s) is then input into a neural network which has been trained to produce a high-quality (in-focus) two-dimensional projection image of the sample.
    Type: Grant
    Filed: July 22, 2020
    Date of Patent: August 23, 2022
    Assignee: Sartorius BioAnalytical Instruments, Inc.
    Inventors: Timothy Jackson, Rickard Sjögren, Christoffer Edlund, Edvin Forsgren
  • Publication number: 20220026699
    Abstract: A method is disclosed for acquiring a single, in-focus two-dimensional projection image of a live, three-dimensional cell culture sample, with a fluorescence microscope. One or more long-exposure “Z-sweep” images are obtained, i.e. via a single or series of continuous acquisitions, while moving the Z-focal plane of a camera through the sample, to produce one or more two-dimensional images of fluorescence intensity integrated over the Z-dimension. The acquisition method is much faster than a Z-stack method, which enables higher throughput and reduces the risk of exposing the sample to too much fluorescent light. The long-exposure Z-sweep image(s) is then input into a neural network which has been trained to produce a high-quality (in-focus) two-dimensional projection image of the sample.
    Type: Application
    Filed: July 22, 2020
    Publication date: January 27, 2022
    Inventors: Timothy JACKSON, Rickard SJÖGREN, Christoffer EDLUND, Edvin FORSGREN