Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/44077
| Título: | Automatic system identification of tissue abnormalities based on 2D B-mode ultrasound images | Autores/as: | Díaz-Suárez, Víctor D. Travieso, Carlos M. González-Fernández, Javier Ferrer, Miguel A. Gómez Déniz, Luis Alonso, Jesus B. |
Clasificación UNESCO: | 3307 Tecnología electrónica | Palabras clave: | Ultrasound tissue-mimicking phantom B-mode imaging database Higuchi Fractal dimension Feed-forward neural network | Fecha de publicación: | 2009 | Editor/a: | 0302-9743 | Publicación seriada: | Lecture Notes in Computer Science | Conferencia: | 12th International Conference on Computer Aided Systems Theory (EUROCAST 2009) 12th International Conference on Computer Aided Systems Theory, EUROCAST 2009 |
Resumen: | A neural network with characteristic parameters to recognize abnormalities in ultrasound images acquired from echographic tissue-mimicking materials is proposed. The neural network has been implemented in MATLAB and it can be used in real time to assist the clinical diagnoses in the early phases. The parameters are extracted from a database of B-mode ultrasound images. After training and testing the network, using a statistically significative set of experimental data and a non-commercial phantom, results show that the proposal can be successfully applied to efficiently deal with this problem. | URI: | http://hdl.handle.net/10553/44077 | ISBN: | 978-3-642-04771-8 3642047718 |
ISSN: | 0302-9743 | DOI: | 10.1007/978-3-642-04772-5_19 | Fuente: | Computer Aided Systems Theory - Eurocast 2009[ISSN 0302-9743],v. 5717, p. 137-+ |
| Colección: | Actas de congresos |
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