Seedings results comparison
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Contents
Key Investigators
- Harvard Medical School: Antonin Perrot-Audet, Kishore Mosaliganti, Sean Megason
- RPI: Badri Roysam, Raghav Padmanabhan
Project
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