Patents by Inventor Ciprian Crainiceanu

Ciprian Crainiceanu 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 of analyzing multi-sequence MRI data for analysing brain abnormalities in a subject
    Patent number: 9888876
    Abstract: The present invention, referred to as Oasis is Automated Statistical Inference for Segmentation (OASIS), is a fully automated and robust statistical method for cross-sectional MS lesion segmentation. Using intensity information from multiple modalities of MRI, a logistic regression model assigns voxel-level probabilities of lesion presence. The OASIS model produces interpretable results in the form of regression coefficients that can be applied to imaging studies quickly and easily. OASIS uses intensity-normalized brain MRI volumes, enabling the model to be robust to changes in scanner and acquisition sequence. OASIS also adjusts for intensity inhomogeneities that preprocessing bias field correction procedures do not remove, using BLUR volumes. This allows for more accurate segmentation of brain areas that are highly distorted by inhomogeneities, such as the cerebellum.
    Type: Grant
    Filed: March 21, 2013
    Date of Patent: February 13, 2018
    Assignees: The Johns Hopkins University, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., The United States of America, as Represented by the Secretary, Department of Health and Human Services
    Inventors: Ciprian Crainiceanu, Arthur Jeffrey Goldsmith, Dzung Pham, Daniel S. Reich, Navid Shiee, Russell T. Shinohara, Elizabeth M. Sweeney
  • METHOD OF ANALYZING MULTI-SEQUENCE MRI DATA FOR ANALYSING BRAIN ABNORMALITIES IN A SUBJECT
    Publication number: 20150045651
    Abstract: The present invention, referred to as Oasis is Automated Statistical Inference for Segmentation (OASIS), is a fully automated and robust statistical method for cross-sectional MS lesion segmentation. Using intensity information from multiple modalities of MRI, a logistic regression model assigns voxel-level probabilities of lesion presence. The OASIS model produces interpretable results in the form of regression coefficients that can be applied to imaging studies quickly and easily. OASIS uses intensity-normalized brain MRI volumes, enabling the model to be robust to changes in scanner and acquisition sequence. OASIS also adjusts for intensity inhomogeneities that preprocessing bias field correction procedures do not remove, using BLUR volumes. This allows for more accurate segmentation of brain areas that are highly distorted by inhomogeneities, such as the cerebellum.
    Type: Application
    Filed: March 21, 2013
    Publication date: February 12, 2015
    Inventors: Ciprian Crainiceanu, Arthur Jeffrey Goldsmith, Dzung Pham, Daniel S. Reich, Navid Shiee, Russell T. Shinohara, Elizabeth M. Sweeney