http://www.cnr.it/ontology/cnr/individuo/prodotto/ID14498
An Ontology-Based Technique for Validation of MRI Brain Segmentation Methods (Articolo in rivista)
- Type
- Label
- An Ontology-Based Technique for Validation of MRI Brain Segmentation Methods (Articolo in rivista) (literal)
- Anno
- 2007-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1007/978-3-540-76888-3_79 (literal)
- Alternative label
Bruno Alfano, Marco Comerci, Giuseppe De Pietro, Amalia Esposito (2007)
An Ontology-Based Technique for Validation of MRI Brain Segmentation Methods
in Lecture notes in computer science
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Bruno Alfano, Marco Comerci, Giuseppe De Pietro, Amalia Esposito (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Note
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- National Research Council (CNR)
Biostructure and Bioimaging Institute (IBB)
via Pansini 5 - 80131 - Napoli, Italy
Institute for High-Performance Computing and Networking (ICAR)
via Pietro Castellino 111 - 80131 - Napoli, Italy (literal)
- Titolo
- An Ontology-Based Technique for Validation of MRI Brain Segmentation Methods (literal)
- Abstract
- We propose an ontology and rules based approach as innovative instrument to improve and validate brain segmentation in Magnetic Resonance Imaging (MRI), which is a very difficult and time consuming problem. Different techniques are realized to automate segmentation and their development requires a careful evaluation of precision and accuracy. At present segmentation procedures are generally validated by comparison with brain atlas or by use of phantoms. We combine ontology and rules to formalize knowledge about normal and anomalous distribution of brain tissues. Automatic reasoning points out possible \"anomalies\", imputable to segmentation procedure: in this way the detection and the subsequent solution of bugs become viable. (literal)
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