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

Khaled Alsaih 1 Guillaume Lemaître 1 Joan Massich Vall 1 Mojdeh Rastgoo 1 Désiré Sidibé 1 Tien Y Wong 2 Ecosse Lamoureux 2 Dan Milea 2 Carol Y. Cheung 2 Fabrice Mériaudeau 1
1 Le2i - Laboratoire Electronique, Informatique et Image
2 Singapore Eye Research Institute, Singapore National Eye Centre
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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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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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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