MIRACLE at ImageCLEFanot 2007: Machine Learning Experiments on Medical Image Annotation Articles uri icon

authors

  • LANA SERRANO, SARA
  • VILLENA ROMAN, JULIO
  • GONZALEZ CRISTOBAL, JOSE CARLOS
  • GOÑI-MENOYO, JOSE MIGUEL

publication date

  • September 2008

start page

  • 597

end page

  • 600

volume

  • 5152

International Standard Serial Number (ISSN)

  • 0302-9743

Electronic International Standard Serial Number (EISSN)

  • 1611-3349

abstract

  • This paper describes the participation of MIRACLE research consortium at the ImageCLEF Medical Image Annotation task of ImageCLEF 2007. Our areas of expertise do not include image analysis, thus we approach this task as a machine-learning problem, regardless of the domain. FIRE is used as a black-box algorithm to extract different groups of image features that are later used for training different classifiers based on kNN algorithm in order to predict the IRMA code. The main idea behind the definition of our experiments is to evaluate whether an axis-by-axis prediction is better than a prediction by pairs of axes or the complete code, or vice versa.