Fully automatic shape modelling using growing cell neural networks

Authors:
Luca Ferrarini;Hans Olofsen;Mark A. van Buchem;Johan H. C. Reiber;Faiza Admiraal-Behloul
Affiliations:
LKEB - Leiden University Medical Center, The Netherlands;LKEB - Leiden University Medical Center, The Netherlands;LKEB - Leiden University Medical Center, The Netherlands;LKEB - Leiden University Medical Center, The Netherlands;LKEB - Leiden University Medical Center, The Netherlands
Venue:
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Year:
2005

Citing 5
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Abstract

In this paper, we present a new framework for shape modelling and analysis: we suggest to look at the problem from a pattern recognition point of view, and claim that under this prospective several advantages are achieved. The modelling of a surface with a point distribution model is seen as an unsupervised clustering problem, and tackled by using growing cell structures. The adaptation of a model to new shapes is studied as a classification task, and provides a straightforward solution to the point correspondence problem in active shape modelling. The method is illustrated and tested in 3D synthetic datasets and applied to the modelling of brain ventricles in an elderly population.