Pleomorphic adenomas (PA) and Warthin tumors (WT) are the most common salivary gland tumors. It exhibits very similar characteristics, which make very difficult to distinguish them. To differentiate these it is necessary due that it strongly influences the surgical procedure and treatment. In this paper, we propose the use of radiomic analysis for discriminating PA and WT based on T1 and T2 Magnetic Resonance Images. The proposed approach starts with the extraction of a large number of quantitative features of delineated tumors from both T1 and T2 sequences, then a feature selector is used for selecting the most discriminative, which are used for training an SVM classification model, whose parameters are optimally selected using the Particle Swarm Optimization algorithm. The proposed approach is able to discriminate between PA and WT tumors with a sensitivity of 91.57± 11.07 and specificity of 89.50 ±11.07, making this a promising method to characterizing and classifying parotid gland tumors.
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