Title :
Topological Well-Composedness and Glamorous Glue: A Digital Gluing Algorithm for Topologically Constrained Front Propagation
Author :
Tustison, Nicholas J. ; Avants, Brian B. ; Siqueira, Marcelo ; Gee, James C.
Author_Institution :
Radiol., Univ. of Virginia, Charlottesville, VA, USA
fDate :
6/1/2011 12:00:00 AM
Abstract :
We propose a new approach to front propagation algorithms based on a topological variant of well-composedness which contrasts with previous methods based on simple point detection. This provides for a theoretical justification, based on the digital Jordan separation theorem, for digitally “gluing” evolved well-composed objects separated by well-composed curves or surfaces. Additionally, our framework can be extended to more relaxed topologically constrained algorithms based on multisimple points. For both methods this framework has the additional benefit of obviating the requirement for both a user-specified connectivity and a topologically-consistent marching cubes/squares algorithm in meshing the resulting segmentation.
Keywords :
image segmentation; digital Jordan separation theorem; digital gluing algorithm; glamorous glue; simple point detection; topological constrained front propagation algorithm; topologically-consistent marching cubes-square algorithm; well-composedness topological variant; Algorithm design and analysis; Artificial neural networks; Image segmentation; Law; Level set; Topology; Digital Jordan separation theorem; front propagation; marching cubes; simple point; topological well-composedness; Algorithms; Artificial Intelligence; Image Enhancement; Image Interpretation, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Subtraction Technique;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2010.2095021