title: Brain volumes characterisation using hierarchical neural networks.
abstract: Objective knowledge of tissue density distribution in CT/MRI brain datasets can be related to anatomical or neuro-functional regions for assessing pathologic conditions characterised by slight differences. The process of monitoring illness and its treatment could be then improved by a suitable detection of these variations. In this paper, we present an approach for three-dimensional (3D) classification of brain tissue densities based on a hierarchical artificial neural network (ANN) able to classify the single voxels of the examined datasets. The method developed was tested on case studies selected by an expert neuro-radiologist and consisting of both normal and pathological conditions. The results obtained were submitted for validation to a group of physicians and they judged the system to be really effective in practical applications.
authors.affiliation: Institute of Information Science and Technologies, Italian National Research Council, Via G. Moruzzi, 1-56124 Pisa, Italy. dibona@iei.pi.cnr.it
authors.forename: Sergio
authors.initials: S
authors.lastname: Di Bona
authors.forename: Heinrich
authors.initials: H
authors.lastname: Niemann
authors.forename: Gabriele
authors.initials: G
authors.lastname: Pieri
authors.forename: Ovidio
authors.initials: O
authors.lastname: Salvetti
mesh_terms: D000368:Aged; D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology* / Q000473:pathology*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D015203:Reproducibility of Results; D014057:Tomography, X-Ray Computed