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Brain volumes characterization using hierarchical neural networks

Academic Article
Publication Date:
2003
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 thesystem to be really effective in practical applications.
Iris type:
01.01 Articolo in rivista
Keywords:
3D images; Neural Networks; Image Classification; Medical imaging
List of contributors:
DI BONA, Sergio; Pieri, Gabriele; Salvetti, Ovidio
Authors of the University:
PIERI GABRIELE
Handle:
https://iris.cnr.it/handle/20.500.14243/36551
Published in:
ARTIFICIAL INTELLIGENCE IN MEDICINE
Journal
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URL

https://www.sciencedirect.com/science/article/pii/S0933365703000617
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