Memorias de investigación
Ponencias en congresos:
Microcalcifications Detection using PFCM and ANN
Año:2011
Áreas de investigación
  • Ingenierías
Datos
Descripción
This work presents a method to detect Miicrocalcifications in Regions of Interest from digitized mammograms. The method is based mainly on the combination of Image Processing, Pattern Recognition and Artificial Intelligence. The Top-Hat transform is a technique based on mathematical morphology operations that, in this work is used to perform contrast enhancement of microcalcifications in the region of interest. In order to find more or less homogeneous regions in the image, we apply a novel image sub-segmentation technique based on Possibilistic Fuzzy c-Means clustering algorithm. From the original region of interest we extract two window-based features, Mean and Deviation Standard, which will be used in a classifier based on a Artificial Neural Network in order to identify microcalcifications. Our results show that the proposed method is a good alternative in the stage of microcalcifications detection, because this stage is an important part of the early Breast Cancer detection.
Internacional
Si
Nombre congreso
3rd Mexican Workshop on Pattern Recognition 2011
Tipo de participación
960
Lugar del congreso
Cancun, Méxic
Revisores
Si
ISBN o ISSN
0302-9743
DOI
10.1007/978-3-642-21587-2_28
Fecha inicio congreso
29/06/2011
Fecha fin congreso
02/07/2011
Desde la página
260
Hasta la página
268
Título de las actas
Pattern Recognition. Lecture Notes in Computer Science, 2011, Volume 6718/2011
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Antonio Vega Corona Universidad de Guanajuato, México
  • Autor: Joel Quintanilla Dominguez UPM
  • Autor: Benjamín Ojeda Magaña UPM
  • Autor: María Guadalupe Cortina Januchs UPM
  • Autor: Alexis Enrique Marcano Cedeño UPM
  • Autor: Rubén Ruelas Universidad de Guadalajara, México
  • 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