Reference : Biomedical image classification with random subwindows and decision trees
Scientific congresses and symposiums : Paper published in a book
Human health sciences : Multidisciplinary, general & others
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/654
Biomedical image classification with random subwindows and decision trees
English
Marée, Raphaël mailto [Université de Liège - ULg > > GIGA-Management : Plateforme bioinformatique >]
Geurts, Pierre mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Piater, Justus mailto [Université de Liège - ULg > Electrical Engineering and Computer Science > INTELSIG >]
Wehenkel, Louis mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
2005
Computer Vision for Biomedical Image Applications
Springer-Verlag Berlin
Lecture Notes in Computer Science 3765
220-229
Yes
No
International
978-3-540-29411-5
Berlin
Computer Vision for Biomedical Image Applications
Beijing
China
[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.
http://hdl.handle.net/2268/654
10.1007/11569541_23

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