MIRACLE at ImageCLEFannot 2008: Nearest Neighbour Classification of Image Feature Vectors for Medical Image Annotation

Lana Serrano, Sara and Villena Román, Julio and González Cristóbal, José Carlos and Goñi Menoyo, José Miguel (2009). MIRACLE at ImageCLEFannot 2008: Nearest Neighbour Classification of Image Feature Vectors for Medical Image Annotation. In: "Evaluating Systems for Multilingual and Multimodal Information Access". Lecture Notes in Computer Science (5706). Springer, Berlin, Alemania, pp. 728-731. ISBN 978-3-642-04446-5. https://doi.org/10.1007/978-3-642-04447-2_93.

Description

Title: MIRACLE at ImageCLEFannot 2008: Nearest Neighbour Classification of Image Feature Vectors for Medical Image Annotation
Author/s:
  • Lana Serrano, Sara
  • Villena Román, Julio
  • González Cristóbal, José Carlos
  • Goñi Menoyo, José Miguel
Item Type: Book Section
Event Title: 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008
Event Dates: 17/09/2008-19/09/2008
Event Location: Aarhus, Dinamarca
Title of Book: Evaluating Systems for Multilingual and Multimodal Information Access
Date: 2009
ISBN: 978-3-642-04446-5
Subjects:
Faculty: E.U.I.T. Telecomunicación (UPM)
Department: Ingeniería y Arquitecturas Telemáticas [hasta 2014]
UPM's Research Group: Grupo de Sistemas Inteligentes
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

This paper describes the participation of MIRACLE research consortium at the ImageCLEF Medical Image Annotation task of ImageCLEF 2008. During the last year, our own image analysis system was developed, based on MATLAB. This system extracts a variety of global and local features including histogram, image statistics, Gabor features, fractal dimension, DCT and DWT coefficients, Tamura features and co-occurrence matrix statistics. A classifier based on the k-Nearest Neighbour algorithm is trained on the extracted image feature vectors to determine the IRMA code associated to a given image. The focus of our participation was mainly to test and evaluate this system in-depth and to compare among diverse configuration parameters such as number of images for the relevance feedback to use in the classification module...

More information

Item ID: 1479
DC Identifier: http://oa.upm.es/1479/
OAI Identifier: oai:oa.upm.es:1479
DOI: 10.1007/978-3-642-04447-2_93
Official URL: http://www.springerlink.com/content/mq10174797220625/
Deposited by: José Miguel Goñi Menoyo
Deposited on: 13 Jul 2012 11:00
Last Modified: 22 Dec 2017 10:01
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