Segmentation of Lateral Ventricles in Magnetic Resonance Images

BOUCHET, A.; PASTORE, J. I.; BRUN, M.; BALLARIN, V.

IFMBE PROCEEDINGS

Springer

Lugar: Berlin Heidelberg; Año: 2015 vol. 49 p. 457 - 460

1680-0737

Magnetic Resonance Imaging is a powerful tool for the early diagnosis of different neurologic diseases. Given that this kind of images have high noise levels and imprecision in the definition of their structures, in this work we propose the use of Compensatory Fuzzy Mathematical Morphology to improve the segmentation of lateral ventricles, compared to Mathematical Morphology. To compare their performance we implement a classic Mathematical Morphology and a Compen-satory Fuzzy Mathematical Morphology version of a segmen-tation algorithm. Once designed the algorithm, we evaluate the results obtained from the use of each methodology. Their per-formance is studied on a 160 images set, containing gold-standard images, provided by the FLENI institute, displaying a correct detection of 94.71% for Mathematical Morphology and 97.46% for Compensatory Fuzzy Mathematical Morphology.