Document - Brain volumes characterization using hierarchical neural networks

2003

Journal article Open Access

Brain volumes characterization using hierarchical neural networks

Di Bona S., Niemann H., Pieri G., Salvetti O.

Image Classification Medical imaging 3D images Artificial Intelligence Medicine (miscellaneous) Neural Networks

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.

Source: Artificial intelligence in medicine (Print) 28 (2003): 307–322. doi:10.1016/S0933-3657(03)00061-7

Publisher: Elsevier Science Publishers, Tecklenburg , Paesi Bassi

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@article{oai:it.cnr:prodotti:43686,
	title = {Brain volumes characterization using hierarchical neural networks},
	author = {Di Bona S. and Niemann H. and Pieri G. and Salvetti O.},
	publisher = {Elsevier Science Publishers, Tecklenburg , Paesi Bassi},
	doi = {10.1016/s0933-3657(03)00061-7},
	journal = {Artificial intelligence in medicine (Print)},
	volume = {28},
	pages = {307–322},
	year = {2003}
}