Fuzzy C-Means Segmentation on Brain MR Slices Corrupted by RF-Inhomogeneity

Authors:
Edoardo Ardizzone;Roberto Pirrone;Orazio Gambino
Affiliations:
Universita' degli Studi di Palermo, DINFO - Dipartimento di Ingegneria Informatica, viale delle Scienze - Edificio 6 - Terzo piano, 90128 Palermo,;Universita' degli Studi di Palermo, DINFO - Dipartimento di Ingegneria Informatica, viale delle Scienze - Edificio 6 - Terzo piano, 90128 Palermo,;Universita' degli Studi di Palermo, DINFO - Dipartimento di Ingegneria Informatica, viale delle Scienze - Edificio 6 - Terzo piano, 90128 Palermo,
Venue:
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Year:
2007

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Abstract

Brain MR Images corrupted by RF-Inhomogeneity exhibit brightness variations in such a way that a standard Fuzzy C-Means (fcm) segmentation algorithm fails. As a consequence, modified versions of the algorithm can be found in literature, which take into account the artifact. In this work we show that the application of a suitable pre-processing algorithm, already presented by the authors, followed by a standard fcmsegmentation achieves good results also. The experimental results ones are compared with those obtained using SPM5, which can be considered the state of the art algorithm oriented to brain segmentation and bias removal.