PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Di Bona S., Niemann H., Pieri G., Salvetti O. Brain volumes characterization using hierarchical neural networks. In: Artificial Intelligence in Medicine, vol. 28 (3) pp. 307 - 322. Elsevier, 2003.
 
 
Abstract
(English)
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 thesystem to be really effective in practical applications.
Subject neural networks
I.5.2 Design Methodology
I.5.1 Models
I.2.10 Vision and Scene Understanding


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