Brain volumes characterisation using hierarchical neural networks

Authors:
Sergio Di Bona;Heinrich Niemann;Gabriele Pieri;Ovidio Salvetti
Affiliations:
Institute of Information Science and Technologies, Italian National Research Council, Via G. Moruzzi, 1-56124 Pisa, Italy;Bavarian Research Center for Knowledge-Based Systems Haberstrasse, 2-D-91058 Erlangen, Germany;Institute of Information Science and Technologies, Italian National Research Council, Via G. Moruzzi, 1-56124 Pisa, Italy;Institute of Information Science and Technologies, Italian National Research Council, Via G. Moruzzi, 1-56124 Pisa, Italy
Venue:
Artificial Intelligence in Medicine
Year:
2003

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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.