Abstract
Feature detection on MR images has largely relied on intensity classification and gradient-based magnitudes. In this paper, we propose the use of phase congruency as a more robust detection method, as it is based on a multiscale intensity-invariant measure. We show the application of phase congruency for the detection of cortical sulci from T2 weighted MRI. Sulci represent important landmarks in the structural analysis of the brain, as their location and orientation provide valuable information for diagnosis and surgical planning. Results show that phase congruency outperforms previous techniques, even in the presence of intensity bias fields due to magnetic field inhomogeneity.
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Linguraru, M.G., González Ballester, M.Á., Ayache, N. (2003). A Multiscale Feature Detector for Morphological Analysis of the Brain. In: Ellis, R.E., Peters, T.M. (eds) Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003. MICCAI 2003. Lecture Notes in Computer Science, vol 2879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39903-2_90
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DOI: https://doi.org/10.1007/978-3-540-39903-2_90
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