An ensemble learning approach for brain cancer detection exploiting radiomic features.

Journal: Computer methods and programs in biomedicine
Published Date: Oct 22, 2019

Abstract

BACKGROUND AND OBJECTIVE: The brain cancer is one of the most aggressive tumour: the 70% of the patients diagnosed with this malignant cancer will not survive. Early detection of brain tumours can be fundamental to increase survival rates. The brain cancers are classified into four different grades (i.e., I, II, III and IV) according to how normal or abnormal the brain cells look. The following work aims to recognize the different brain cancer grades by analysing brain magnetic resonance images.

Authors

  • Luca Brunese
    Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, Campobasso, Italy.
  • Francesco Mercaldo
    Institute for Informatics and Telematics, National Research Council of Italy (CNR), Pisa, Italy; Department of Biosciences and Territory, University of Molise, Pesche (IS), Italy. Electronic address: francesco.mercaldo@iit.cnr.it.
  • Alfonso Reginelli
    Department of Precision Medicine, University of Campania "Luigi Vanvitelli", Napoli, Italy.
  • Antonella Santone
    Department of Biosciences and Territory, University of Molise, Pesche (IS), Italy.

Keywords

External Resources

Popular Topics
Recent Journals