Giorgio
De Nunzio1,2, Antonella Castellano3,4, Gabriella
Pastore, 1,2, Marina Donativi2, Giuseppe Scotti3,
Lorenzo Bello5, Andrea Falini6
1INFN (National Institute of Nuclear
Physics), Lecce, Italy; 2Department of Materials Science,
University of Salento, Lecce, Italy; 3Neuroradiology Unit and
CERMAC, Scientific Institute and University Vita-Salute San Raffaele, Milan,
Italy; 4Institute of Radiological Sciences, University of Milano,
Milan, Italy; 5Neurosurgery, Department of Neurological Sciences,
University of Milano, Milan, Italy; 6Neuroradiology Unit and
CERMAC, , Scientific Institute and University Vita-Salute San Raffaele,
Milan, Italy
This
work illustrates the development and validation of a semi-automated
Computer-Assisted Detection technique (CAD) for the recognition of cerebral
glioma in Diffusion Tensor MR images (DTI-MR). The described system adheres
to the classic scheme of a CAD software tool, with a data preprocessing step
followed by feature calculation and supervised tissue classification. The
chosen discriminating features come from 3D statistical Texture Analysis.
Segmentation results are also correlated with histopathological findings from
specimens obtained from image-guided tumor biopsies.