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An Ontology Approach for Classification of Abnormal White Matter in Patients with Multiple Sclerosis

  • Bruno Alfano
  • Arturo Brunetti
  • Giuseppe De Pietro
  • Amalia Esposito
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4799)

Abstract

Multiple Sclerosis (MS) is an inflammatory autoimmune disease of the Central Nervous System, characterized by development of lesions that cause interference in the communication between brain and the rest of the body. Some techniques using numeric algorithms based on mathematical and probabilistic theories are generally used in order to obtain lesions detection. In this paper we describe an innovative approach for lesions recognition to be applied after segmentation of brain tissues from quantitive evaluation of MR studies. Knowledge about MS lesions is formalized through an ontology and a set of rules: integrating them, automatic inferences can be realized to point out lesions, starting from data about potentially brain abnormal white matter.

Keywords

Multiple Sclerosis Lesion Detection Medical Ontology Rules Reasoning 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Bruno Alfano
    • 1
  • Arturo Brunetti
    • 2
  • Giuseppe De Pietro
    • 3
  • Amalia Esposito
    • 3
  1. 1.National Research Council (CNR), Biostructure and Bioimaging Institute (IBB), via Pansini 5 – 80131 – NapoliItaly
  2. 2.University “Federico II”, Department of Biomorphological and Functional Sciences, via Pansini 5 – 80131 – NapoliItaly
  3. 3.National Research Council (CNR), Institute for High-Performance Computing and Networking (ICAR), via Pietro Castellino 111 – 80131 – NapoliItaly

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