DocumentCode :
1263373
Title :
Classification of Endomicroscopic Images of the Lung Based on Random Subwindows and Extra-Trees
Author :
Désir, Chesner ; Petitjean, Caroline ; Heutte, Laurent ; Salaün, Mathieu ; Thiberville, Luc
Author_Institution :
LITIS EA 4108, Université de Rouen, France
Volume :
59
Issue :
9
fYear :
2012
Firstpage :
2677
Lastpage :
2683
Abstract :
Recently, the in vivo imaging of pulmonary alveoli was made possible thanks to confocal microscopy. For these images, we wish to aid the clinician by developing a computer-aided diagnosis system, able to discriminate between healthy and pathological subjects. The lack of expertise currently available on these images has first led us to choose a generic approach, based on pixel-value description of randomly extracted subwindows and decision tree ensemble for classification (extra-trees). In order to deal with the great complexity of our images, we adapt this method by introducing a texture-based description of the subwindows, based on local binary patterns. We show through our experimental protocol that this adaptation is a promising way to classify fibered confocal fluorescence microscopy images. In addition, we introduce a rejection mechanism on the classifier output to prevent nondetection errors.
Keywords :
Decision trees; Feature extraction; Lungs; Pathology; Training; Vectors; Vegetation; Confocal fluorescence microscopy; extra-trees; image classification; medical imaging; reject rule; Algorithms; Databases, Factual; Decision Trees; Diagnosis, Computer-Assisted; Humans; Microscopy, Confocal; Pulmonary Alveoli; Reproducibility of Results; Smoking; Thoracoscopy;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2012.2204747
Filename :
6266708
Link To Document :
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