Reference : Random subwindows and extremely randomized trees for image classification in cell biology
Scientific journals : Article
Life sciences : Anatomy (cytology, histology, embryology...) & physiology
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/655
Random subwindows and extremely randomized trees for image classification in cell biology
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 >]
Wehenkel, Louis mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
2007
BMC Cell Biology
Biomed Central Ltd
8
Suppl. 1
Yes (verified by ORBi)
International
1471-2121
London
[en] Bioinformatics ; Image Classification ; Computer Vision
[en] Background: With the improvements in biosensors and high-throughput image acquisition technologies, life science laboratories are able to perform an increasing number of experiments that involve the generation of a large amount of images at different imaging modalities/scales. It stresses the need for computer vision methods that automate image classification tasks. Results: We illustrate the potential of our image classification method in cell biology by evaluating it on four datasets of images related to protein distributions or subcellular localizations, and red-blood cell shapes. Accuracy results are quite good without any specific pre-processing neither domain knowledge incorporation. The method is implemented in Java and available upon request for evaluation and research purpose. Conclusion: Our method is directly applicable to any image classification problems. We foresee the use of this automatic approach as a baseline method and first try on various biological image classification problems.
Giga-Systems Biology and Chemical Biology
Fonds Européen de Développement Régional - FEDER ; Fonds de la Recherche Scientifique (Communauté française de Belgique) - F.R.S.-FNRS
http://hdl.handle.net/2268/655
10.1186/1471-2121-8-S1-S2
http://www.biomedcentral.com/1471-2121/8/S1/S2

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