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Segmentation and mesh mapping method for cardiac tissue layers from 4-D OCT images

eagle-i ID

http://ohsu.eagle-i.net/i/0000013a-74e1-44d9-b332-51b580000000

Resource Type

  1. Algorithmic software component

Properties

  1. Related grant number
    NIH R01 HL094570
  2. Related grant number
    NSF DBI-1052688
  3. Resource Description
    "This algorithm-driven software is designed to extract the dynamic shapes of the heart myocardium and endocardium from reconstructed 4-D optical coherence tomography images. For the Rugonyi Lab's uses, images of three surfaces are collected over time: the external and internal surfaces of the myocardium layer and the endocardium (or tissue-lumen interface) surface. To detect cardiac tissues, several layer 2-D meshes are placed around the myocardium and several 2-D edge meshes are placed around the endocardium. The meshes on each tissue layer are then linked together using active-contour techniques, and detection of the myocardial and endocardial layers is guided by a robust maximum-likelihood estimator. Linking the meshes with active-contour facilitates detection and tracking of tissue motion."
  4. Contact
    Rugonyi, Sandra, Ph.D.
  5. Used by
    Sandra Rugonyi Laboratory
  6. Data Input
    2-D optical coherence tomography images of heart tissue
  7. Data Output
    3-D deformable mesh model of heart
  8. Software purpose
    Image processing objective
  9. Related Technique
    Doppler OCT
  10. Developed by
    Yin, Xin, Ph.D.
  11. Algorithm used
    Expectation-Maximization(EM) algorithm
  12. Coded in
    C++
 
RDFRDF
 
Provenance Metadata About This Resource Record

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The eagle-i Consortium is supported by NIH Grant #5U24RR029825-02 / Copyright 2016