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A nonparametric, entropy-minimizing MRI tissue classification algorithm implementation using ITK

Tasdizen, Tolga, Awate, Suyash, Whitaker, Ross
University of Utah
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Submitted by Tolga Tasdizen on 2005-08-03T16:33:51Z.

This paper focuses on the role of open-source software in the development of a novel magnetic resonance image (MRI) tissue classification algorithm. Specifically, we describe the of use existing classes in the Insight Segmentation and Registration Toolkit (ITK) and several new classes that were implemented to perform non-parametric density estimation and entropy minimization. These new classes also provide a general framework for nonparametric density estimation and related applications.