N4ITK: Improved N3 Bias Correction

Nicholas J. Tustison(University of Pennsylvania), Brian Avants(University of Pennsylvania), Philip A. Cook(University of Pennsylvania), Yuanjie Zheng(University of Pennsylvania), Alexander Egan(University of Pennsylvania), Paul A. Yushkevich(University of Pennsylvania), James C. Gee(University of Pennsylvania)
IEEE Transactions on Medical Imaging
April 9, 2010
Cited by 6,352

Abstract

A variant of the popular nonparametric nonuniform intensity normalization (N3) algorithm is proposed for bias field correction. Given the superb performance of N3 and its public availability, it has been the subject of several evaluation studies. These studies have demonstrated the importance of certain parameters associated with the B-spline least-squares fitting. We propose the substitution of a recently developed fast and robust B-spline approximation routine and a modified hierarchical optimization scheme for improved bias field correction over the original N3 algorithm. Similar to the N3 algorithm, we also make the source code, testing, and technical documentation of our contribution, which we denote as "N4ITK," available to the public through the Insight Toolkit of the National Institutes of Health. Performance assessment is demonstrated using simulated data from the publicly available Brainweb database, hyperpolarized (3)He lung image data, and 9.4T postmortem hippocampus data.


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