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

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Résumé

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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Dates et versions

hal-01320212 , version 1 (24-05-2016)

Identifiants

  • HAL Id : hal-01320212 , version 1

Citer

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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