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I-DO: A Deformable Organisms framework for ITK

McIntosh, Chris, Hamarneh, Ghassan
Medical Image Analysis Lab, Simon Fraser University
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/228
New: Prefer using the following doi: https://doi.org/10.54294/2mw8nl
Submitted by Chris Mcintosh on 2006-07-14T01:29:45Z.

Medical image analysis is an important problem relating to the study of various diseases. Since their inception to MICCAI in 2001, ''deformable organisms'' have emerged as a fruitful methodology with examples ranging from 2D corpus callosum segmentation to 3D vasculature and spinal cord segmentation. Essentially we have developed an artificial life framework that complements classical deformable models (snakes and deformable meshes) with high-level, anatomically-driven control mechanisms. This paper describes the integration of deformable organisms into the Insight Toolkit (ITK) \url{www.itk.org}. Our code attempts to bridge the ITK framework and coding style with deformable organism design methodologies. In the interest of open science, as the framework develops it will serve as a basis for the community to develop new deformable organisms as well as experiment with those recently published by our group.