Classification of SD-OCT volumes with multi pyramids, LBP and HOG descriptors: application to DME detections
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.
Origine | Fichiers produits par l'(les) auteur(s) |
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