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Biomedical image classification with random subwindows and decision trees
Marée, Raphaël; Geurts, Pierre; Piater, Justus et al.
2005In Computer Vision for Biomedical Image Applications
Peer reviewed
 

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Abstract :
[en] In this paper, we address a problem of biomedical image classification that involves the automatic classification of x-ray images in 57 predefined classes with large intra-class variability. To achieve that goal, we apply and slightly adapt a recent generic method for image classification based on ensemble of decision trees and random subwindows. We obtain classification results close to the state of the art on a publicly available database of 10000 x-ray images. We also provide some clues to interpret the classification of each image in terms of subwindow relevance.
Disciplines :
Computer science
Human health sciences: Multidisciplinary, general & others
Author, co-author :
Marée, Raphaël  ;  Université de Liège - ULiège > GIGA-Management : Plateforme bioinformatique
Geurts, Pierre ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Piater, Justus ;  Université de Liège - ULiège > Electrical Engineering and Computer Science > INTELSIG
Wehenkel, Louis  ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Language :
English
Title :
Biomedical image classification with random subwindows and decision trees
Publication date :
2005
Event name :
Computer Vision for Biomedical Image Applications
Event place :
Beijing, China
Audience :
International
Main work title :
Computer Vision for Biomedical Image Applications
Publisher :
Springer-Verlag Berlin, Berlin, Germany
ISBN/EAN :
978-3-540-29411-5
Collection name :
Lecture Notes in Computer Science 3765
Pages :
220-229
Peer reviewed :
Peer reviewed
Available on ORBi :
since 07 October 2008

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