Microcalcifications Detection using PFCM and ANN

Vega Corona, Antonio and Quintanilla Domínguez, Joel and Ojeda Magaña, Benjamín and Cortina Januchs, María Guadalupe and Marcano Cedeño, Alexis Enrique and Ruelas, Rubén and Andina de la Fuente, Diego (2011). Microcalcifications Detection using PFCM and ANN. In: "Third Mexican Conference, MCPR 2011", 29/06/2011 - 02/07/2011, Cancún, México. ISBN 978-3-642-21586-5. pp. 260-268. https://doi.org/10.1007/978-3-642-21587-2_28.


Title: Microcalcifications Detection using PFCM and ANN
  • Vega Corona, Antonio
  • Quintanilla Domínguez, Joel
  • Ojeda Magaña, Benjamín
  • Cortina Januchs, María Guadalupe
  • Marcano Cedeño, Alexis Enrique
  • Ruelas, Rubén
  • Andina de la Fuente, Diego
Item Type: Presentation at Congress or Conference (Article)
Event Title: Third Mexican Conference, MCPR 2011
Event Dates: 29/06/2011 - 02/07/2011
Event Location: Cancún, México
Title of Book: Pattern Recognition. Lecture Notes in Computer Science
Date: 2011
ISBN: 978-3-642-21586-5
Volume: 6718/2
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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This work presents a method to detect Microcalcifications 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

More information

Item ID: 13271
DC Identifier: https://oa.upm.es/13271/
OAI Identifier: oai:oa.upm.es:13271
DOI: 10.1007/978-3-642-21587-2_28
Official URL: http://link.springer.com/chapter/10.1007%2F978-3-6...
Deposited by: Memoria Investigacion
Deposited on: 28 Nov 2012 10:26
Last Modified: 21 Apr 2016 12:36
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