Segmentation of brain tumors using a semi-automatic computational strategy
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Fecha
2019
Autores
Vera, M.
Huérfano, Y.
Gelvez, E.
Valbuena, O.
Salazar, J.
Molina, V.
Vera, M I.
Salazar, W.
Sáenz, F.
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Editor
IOP Publishing
Resumen
In this work, a semi-automatic computational strategy is proposed for brain tumor
segmentation. The filtering (erosion + gaussian filters), segmentation (level set technique) and
quantification (BT volume) stages are applied to magnetic resonance imaging in order to
generate the three-dimensional morphology of brain tumors. The Jaccard's Similarity Index is
considered to contrast manual segmentation with semi-automatic segmentations of brain tumor.
In this sense, the highest Jaccard's Similarity Index provides the best parameters of the
techniques that constitute the semi-automatic computational strategy. Results are promising,
showing an excellent correlation between these segmentations. The volume is used for the brain
tumors characterization.
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Palabras clave
Head - Tumors, Magnetic resonance, Jaccard