Seedings results comparison

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Key Investigators

  • Harvard Medical School: Antonin Perrot-Audet, Kishore Mosaliganti, Sean Megason
  • RPI: Badri Roysam, Raghav Padmanabhan

Project

Seed.png

Objective

  • Improve segmentation algorithms initialization for nuclei detection in 3D fluorescent microscopy:
    • get a better accuracy,
    • improve computation speed.

Approach, Plan

  • Compare different algorithms,
  • Find a measure to evaluate different algorithm results,
  • Fusion output of several algorithms.

Progress

  • Implemented algorithms in ITK:
    • Radial voting,
    • Multi-scale Distance Map weighted Laplacian of Gaussian.
  • Created a collaboration framework using ITK:
    • Set of utilities for input images normalization
    • Developed a windowed local maxima filter
  • Evaluated and compared output of on synthetic 2D data & 3D Nuclei channel from Megason Lab
    • Multi-scale Distance Map weighted Laplacian of Gaussian.
    • Radial voting

Next

  • Implement state of the art seeding algorithms with ITK
    • gradient flow tracking
  • Evaluate new algorithms

Ressources

  • Source code :
git@github.com:antonin07130/NAMICSeeding.git

We shall use git for version control : A small introduction to git : here

  • Data set :
Non public