Abstract
The use of Magnetic Resonance as a supporting tool in the diagnosis and monitoring of Multiple Sclerosis and in the assessment of treatment effects requires the accurate classification of cerebral white matter lesions. In order to support neuroradiologists in this task, this paper presents an advanced Decision Support System devised to: (i) encode the expert’s medical knowledge in terms of linguistic variables, linguistic values, and fuzzy rules; (ii) implement a fuzzy inference technique able to best fit the expert’s decision-making process to identify MS lesions; (iii) employ an adaptive fuzzy technique to tune the shapes of the membership functions for each linguistic variable involved in the rules. The performance of the DSS is quantitatively evaluated on 120 patients affected by MS.
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De Falco, I., Esposito, M., De Pietro, G. (2013). An Advanced DSS for Classification of Multiple-Sclerosis Lesions in MR Images. In: Sobh, T., Elleithy, K. (eds) Emerging Trends in Computing, Informatics, Systems Sciences, and Engineering. Lecture Notes in Electrical Engineering, vol 151. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3558-7_32
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DOI: https://doi.org/10.1007/978-1-4614-3558-7_32
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