Biomedical Imaging Modality Classification Using Bags of Visual and Textual Terms with Extremely Randomized Trees: Report of ImageCLEF 2010 Experiments

Marée, Raphaël; Stern, Olivier; Geurts, Pierre

Paper published in a book (Scientific congresses and symposiums)

Marée, Raphaël; Stern, Olivier; Geurts, Pierre

2010 • In CLEF 2010: Padua, Italy - Notebook Papers/LABs/Workshops

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https://hdl.handle.net/2268/82992

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Abstract :

[en] In this paper we describe our experiments related to the ImageCLEF 2010 medical modality classification task using extremely randomized trees. Our best run combines bags of textual and visual features. It yields 90% recognition rate and ranks 6th among 45 runs (ranging from 94% downto 12%).

Research Center/Unit :

Giga-Systems Biology and Chemical Biology - ULiège

Disciplines :

Computer science

Author, co-author :

Marée, Raphaël ; Université de Liège - ULiège > GIGA-Management : Plateforme bioinformatique

Stern, Olivier ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation

Geurts, Pierre ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation

Language :

English

Title :

Biomedical Imaging Modality Classification Using Bags of Visual and Textual Terms with Extremely Randomized Trees: Report of ImageCLEF 2010 Experiments

Publication date :

2010

Event name :

CLEF 2010 LABs and Workshops

Event date :

22-23 September 2010

Audience :

International

Main work title :

CLEF 2010: Padua, Italy - Notebook Papers/LABs/Workshops

Funders :

FEDER - Fonds Européen de Développement Régional
F.R.S.-FNRS - Fonds de la Recherche Scientifique

Available on ORBi :

since 27 January 2011

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Bibliography

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[MGW09] Raphäel Marée, Pierre Geurts, and Louis Wehenkel. Content-based image retrieval by indexing random subwindows with randomized trees. IPSJ Transactions on Computer Vision and Applications, 1(1):46-57, jan 2009.
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