Classification of SD-OCT volumes with multi pyramids, LBP and HOG descriptors: application to DME detections

Abstract : This paper deals with the automated detection of DME on OCT volumes. Our method considers a generic classification pipeline with preprocessing for noise removal and flattening of each B-Scan. Features such as HoG and LBP are extracted and combined to create a set of different feature vectors which are fed to a linear-SVM classifier. Experimental results show a promising sensitivity/specificity of 0.75/0.87 on a challenging dataset.
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Communication dans un congrès
38th IEEE Engineering in Medicine and Biology Society (EMBC), Aug 2016, Orlando, United States
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https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01320212
Contributeur : Guillaume Lemaitre <>
Soumis le : mardi 24 mai 2016 - 16:21:57
Dernière modification le : vendredi 27 mai 2016 - 01:01:40
Document(s) archivé(s) le : jeudi 25 août 2016 - 10:19:39

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  • HAL Id : hal-01320212, version 1

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Khaled Alsaih, Guillaume Lemaître, Joan Massich Vall, Mojdeh Rastgoo, Désiré Sidibé, et al.. Classification of SD-OCT volumes with multi pyramids, LBP and HOG descriptors: application to DME detections. 38th IEEE Engineering in Medicine and Biology Society (EMBC), Aug 2016, Orlando, United States. <hal-01320212>

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