Automatic detection of cranial fractures in radiological images using a pattern classifier

Authors

  • Itzamá López-Yáñez Instituto Politécnico Nacional
  • Rolando Flores-Carapia Instituto Politécnico Nacional
  • Cornelio Yáñez-Márquez Instituto Politécnico Nacional
  • Oscar Camacho-Nieto Instituto Politécnico Nacional

Keywords:

Cranial fractures, radiographic images, pattern classification, alpha-beta associative models

Abstract


In this work, an automatic pattern classification system is presented, whose goal is detecting the presence or absence of fractures in cranial radiographic images. The basis for the proposal is an original coding technique, coupled with an emerging pattern classifier: the Gamma classifier. This proposal draws concepts from three areas of current scientific research: Mathematical Morphology, image histograms, and Alpha-Beta associative models. Also, an experimental study is presented, comparing the performance shown by the system to that exhibited by other pattern classifiers present in current scientific literature. The results obtained are competitive, reaching 94.23% of correct classification.
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Published

2012-11-15

How to Cite

López-Yáñez, I., Flores-Carapia, R., Yáñez-Márquez, C., & Camacho-Nieto, O. (2012). Automatic detection of cranial fractures in radiological images using a pattern classifier. Revista Facultad De Ingeniería Universidad De Antioquia, (61), 29–40. Retrieved from https://revistas.udea.edu.co/index.php/ingenieria/article/view/13535