6533b7d6fe1ef96bd1267064

RESEARCH PRODUCT

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

Roberto PirroneOrazio GambinoEdoardo Ardizzone

subject

Artifact (error)BrightnessComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationPattern recognitionFuzzy logicBrain segmentationSegmentationComputer visionArtificial intelligenceMr imagesbusinessrf-inhomogeneity bias artifact mri fuzzy c-means segmentationHistogram equalization

description

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 fcm segmentation 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.

yearjournalcountryeditionlanguage
2007-08-24
https://doi.org/10.1007/978-3-540-73400-0_48