2014 Project Week:CardiacCongenitalSegmentation

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Home < 2014 Project Week:CardiacCongenitalSegmentation

Key Investigators

Danielle Pace, MIT

Polina Golland, MIT

Project Description

Objective

  • Develop a semi-automatic segmentation algorithm for cardiac MR images of patients with congenital heart defects.
  • Goal is to build a surface model showing the endocardial and epicardial boundaries, for surgical planning.
  • Challenges:
    • Very large inter-subject variability due to heart defects
    • Intensity inhomogeneities within myocardium and blood pool
    • Similar intensity distributions within adjacent tissues (e.g. liver, chest muscle)

Approach, Plan

  • Try existing open-source tools for segmentation and registration on the five datasets that we have so far.
  • See where these methods fail, to focus our efforts for developing algorithms for segmenting hearts with congenital defects.

Progress

  • Focused on blood pool segmentation in one test case. Tried:
    • CARMA tools: isolated connected / connected threshold operators
    • Editor level tracing effect
    • Editor Fast Marching effect
    • Editor Grow Cuts effect
    • Carrera interactive segmentation
    • Robust statistic active contour segmentation
  • Best tool = Carrera interactive segmentation
    • Main difficulty = small chamber/vessel walls assigned as blood pool, but these can be fixed within Carrera somewhat easily
  • Also tried affine registrations across my 5 subjects, using BRAINSFIT
    • Works very roughly, as expected
  • Next steps:
    • Try Carrera on additional datasets for blood pool segmentation
    • Myocardium segmentation is still a challenge
  • Thanks to: Josh Cates, Salma Bengali, Yi Gao, Ivan Kolesov for your help and suggestions!