Encephalic NMR Tumor Diversification by Textural Interpretation
The novel technologies used in different application domains allow to obtain digital images with a high complex informative content. These meaningful information are expressed by textural skin that covers the objects represented inside the images. The textural information can be exploited to interpret the semantic meaning of the images themselves. This paper provides a mathematical characterization, based on texture analysis, of the craniopharyngioma pathology distinguishing it from other kinds of primary cerebral tumors. By this characterization a prototype has been developed, which has primarily allowed to identify potential abnormal masses inside the cerebral tissue and subsequently to possibly classify them as craniopharyngiomas.
KeywordsMedical image texture analysis pattern recognition feature extraction segmentation classification co-occurrence matrix
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