Baseline Results for the ImageCLEF 2007 Medical Automatic Annotation Task Using Global Image Features

Abstract. This paper provides baseline results for the medical automatic annotation task of CLEF 2007 by applying the image retrieval in medical applications (IRMA)-based algorithms previously used in 2005 and 2006, with identical parameterization. Three classifiers based on global image features are combined within a nearest neighbor (NN) approach: texture histograms and two distance measures, which are applied on down-scaled versions of the original images and model common variabilities in the image data. According to the evaluation scheme introduced in 2007, which uses the hierarchical structure of the coding scheme

• Type: Conference
• Year: 2007
• Where: CLEF
• Authors: Mark Oliver Güld, Thomas Martin Deserno
• Keywords: CLEF 2007, Global Image Features, Information Retrieval, Medical Automatic Annotation, Paper Provides Baseline