Novel Methods for Automated Key Image Selection

Information

  • Research Project
  • 6583176
  • ApplicationId
    6583176
  • Core Project Number
    R43MH065764
  • Full Project Number
    1R43MH065764-01A1
  • Serial Number
    65764
  • FOA Number
  • Sub Project Id
  • Project Start Date
    1/15/2003 - 21 years ago
  • Project End Date
    1/31/2004 - 20 years ago
  • Program Officer Name
    GRABB, MARGARET C.
  • Budget Start Date
    1/15/2003 - 21 years ago
  • Budget End Date
    1/31/2004 - 20 years ago
  • Fiscal Year
    2003
  • Support Year
    1
  • Suffix
    A1
  • Award Notice Date
    -
Organizations

Novel Methods for Automated Key Image Selection

[unreadable] DESCRIPTION (provided by the applicant): Significant new knowledge about human behavior and the brain has come to light in recent years, due in part to rapid technical developments in imaging. As the role of imaging becomes increasingly important in neurosciences, effective methods for managing and retrieving images will become even more critical; without such advances, further progress will be hindered. The goal of this proposal is the automated summarization of large imaging sets. Image summarization proffers a method to compress imaging studies by selecting only pertinent image slices that objectively document a patient's condition; as such, its applications include multimedia electronic medical records, telemedicine, and teaching files. In Phase I, development is focused on a customizable brain atlas used for registering patient imaging studies in order to select key images. This phase addresses selection of images from "normal" studies and studies with only subtle morphological changes, as typical of most patients with psychiatric disorders. Automatic techniques for customizing the atlas to imaging study acquisition parameters are developed, in addition to registration methods for mapping the atlas to the patient's original study. Building from this initial work, Phase II expands to encompass selection of images from "abnormal" studies that exhibit gross morphological changes through principle component analysis, further customization of the atlas for different age groups (e.g., pediatric), and incorporation of structured data entry (SDE) and natural language processing (NLP) of medical reports to help guide automatic selection of key images. The resultant product will be a fully automated software system that can select relevant images from any imaging study. Initial evaluation in Phase I will examine the performance of the contrast customizable atlas and summarization/relevant slice selection, as compared to human experts. [unreadable] [unreadable]

IC Name
NATIONAL INSTITUTE OF MENTAL HEALTH
  • Activity
    R43
  • Administering IC
    MH
  • Application Type
    1
  • Direct Cost Amount
  • Indirect Cost Amount
  • Total Cost
    93365
  • Sub Project Total Cost
  • ARRA Funded
  • CFDA Code
    242
  • Ed Inst. Type
  • Funding ICs
    NIMH:93365\
  • Funding Mechanism
  • Study Section
    ZRG1
  • Study Section Name
    Special Emphasis Panel
  • Organization Name
    MEDAXIS CORPORATION
  • Organization Department
  • Organization DUNS
  • Organization City
    LOS ANGELES
  • Organization State
    CA
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    90024
  • Organization District
    UNITED STATES