In this paper we present an approach for the classification of tissue density in three dimensional brain tomographic scans. The proposed approach is based on a hierarchical neural network model able to classify the single voxel of the examined dataset. The results have shown that the method has a good effectiveness in practical applications and that it can be used for designing a full 3D instrument suitable to support the analysis of diseased diagnosis and follow-up.

A multilevel neural network model for density volumes classifications

Pieri G;Salvetti O
2001

Abstract

In this paper we present an approach for the classification of tissue density in three dimensional brain tomographic scans. The proposed approach is based on a hierarchical neural network model able to classify the single voxel of the examined dataset. The results have shown that the method has a good effectiveness in practical applications and that it can be used for designing a full 3D instrument suitable to support the analysis of diseased diagnosis and follow-up.
2001
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
953-96769-4-0
Tissue density variation
Brain tomographic scans
Image processing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/113165
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