Patents by Inventor Niranchana MANIVANNAN

Niranchana MANIVANNAN 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: 20240127446
    Abstract: System/Method/Device for labelling images in an automated manner to satisfy a performance of a different algorithm and then applying active learning to learn a deep learning model which would enable ‘real-time’ operation of quality assessment and with high accuracy.
    Type: Application
    Filed: February 25, 2022
    Publication date: April 18, 2024
    Applicants: Carl Zeiss Meditec, Inc., Carl Zeiss Meditec AG
    Inventors: Homayoun Bagherinia, Aditya Nair, Niranchana Manivannan, Mary Durbin, Lars Omlor, Gary Lee
  • Publication number: 20230140881
    Abstract: A system and method for use with optical coherence tomography (OCT) data to identify a target pathology extracts multiple pathology-characteristic images from the OCT data. The extracted pathology-characteristic images may include a mixture of OCT structural images (including retinal layer thickness information) and OCT angiography images. Optionally, other pathology-characteristic images and data maps (mapped to corresponding positions in the OCT data), such as fundus images and visual field test maps may be accessed as additional pathology-characteristic images. Each pathology-characteristic image defines a different image channel (e.g., “color channel”) per pixel in a composite, channel-coded image, which is then used to train a neural network to search for the target pathology in OCT data. The trained neural network may then receive new composite, channel-coded image and identify/segment the target pathology within the new channel-coded image.
    Type: Application
    Filed: April 28, 2021
    Publication date: May 11, 2023
    Inventors: Luis DE SISTERNES, Niranchana MANIVANNAN
  • Publication number: 20220160228
    Abstract: An ophthalmic imaging system provides an automatic focus mechanism based on the difference of consecutive scan lines. The system also provides of user selection of a focus point within a fundus image. A neural network automatically identifies the optic nerve head in an FA or ICGA image, which may be used to determine fixation angle. The system also provides additional scan tables for multiple imaging modalities to accommodate photophobia patients and multi-spectrum imaging options.
    Type: Application
    Filed: March 18, 2020
    Publication date: May 26, 2022
    Inventors: Conor LEAHY, Jeffrey SCHMIDT, Keith BROCK, Priya KULKARNI, David NOLAN, Keith O'HARA, Matthew J. EVERETT, Michael CHEN, Lars OMLOR, Niranchana MANIVANNAN, Mary DURBIN
  • Publication number: 20220084210
    Abstract: An automated segmentation and identification system/method for identifying geographic atrophy (GA) phenotypic patterns in fundus autofluorescence images. A hybrid process combines a supervised pixel classifier with an active contour algorithm. A trained, machine learning model (e.g., SVM or U-Net) provides initial GA segmentation/classification, and this is followed by Chan-Vese active contour algorithm. The junctional zones of the GA segmented area are then analyzed for geometric regularity and light intensity regularity. A determination of GA phenotype is made, at least in part, from these parameters.
    Type: Application
    Filed: February 6, 2020
    Publication date: March 17, 2022
    Inventors: Niranchana MANIVANNAN, Mary DBUREIN