Memorias de investigación
Artículos en revistas:
Improvement for detection of microcalcifications through clustering algorithms and artificial neural networks
Año:2011

Áreas de investigación
  • Ingenierías,
  • Tecnología electrónica y de las comunicaciones,
  • Sistema informático

Datos
Descripción
A new method for detecting microcalcifications in regions of interest (ROIs) extracted from digitized mammograms is proposed. The top-hat transform is a technique based on mathematical morphology operations and, in this paper, is used to perform contrast enhancement of the mi-crocalcifications. To improve microcalcification detection, a novel image sub-segmentation approach based on the possibilistic fuzzy c-means algorithm is used. From the original ROIs, window-based features, such as the mean and standard deviation, were extracted; these features were used as an input vector in a classifier. The classifier is based on an artificial neural network to identify patterns belonging to microcalcifications and healthy tissue. Our results show that the proposed method is a good alternative for automatically detecting microcalcifications, because this stage is an important part of early breast cancer detection.
Internacional
Si
JCR del ISI
Si
Título de la revista
EURASIP journal on advances in signal processing
ISSN
1687-6172
Factor de impacto JCR
1,01
Información de impacto
Volumen
DOI
10.1186/1687-6180-2011-91
Número de revista
Desde la página
1
Hasta la página
11
Mes
SIN MES
Ranking

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Participantes
  • Autor: Maria Guadalupe Cortina Januchs UPM
  • Autor: Joel Quintanilla Domínguez UPM
  • Autor: Benjamín Ojeda Magaña UPM
  • Autor: Alexis Enrique Marcano Cedeño UPM
  • Autor: Diego Andina De la Fuente UPM

Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Automatización en Señal y Comunicaciones (GASC)
  • Centro o Instituto I+D+i: Centro de tecnología Biomédica CTB
  • Departamento: Señales, Sistemas y Radiocomunicaciones