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
Vista completa

Visitas

95
actualizado el 27-jul-2024

Google ScholarTM

Verifica

Altmetric


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.