Title :
Classification of drusen positions in optical coherence tomography data from patients with age-related macular degeneration
Author :
Dufour, P.A. ; De Zanet, S. ; Wolf-Schnurrbusch, U. ; Kowal, Janusz
Author_Institution :
ARTORG Center for Biomed. Eng. Res., Univ. of Bern, Bern, Switzerland
Abstract :
Quantitative analysis of optical coherence tomography volumes is an important tool for both clinicians and researchers. Until now, most work has focused on segmentation of the intraretinal cell layers, but the segmentation of pathological datasets remains challenging. We propose the application of random forest to detect the locations of drusen in the retinal pigment epithelium. This is an important step for further analysis of optical coherence tomography data, for segmentation or otherwise. The presented combination of Bruch´s Membrane segmentation with subsequent sampling around the retinal pigment epithelium is a way to quickly compute discriminative features for classification. The proposed method achieves an AUC of 0.94 on our test set, while keeping the computational complexity at a minimum. This makes a clinical setup feasible and provides a tool for clinicians and researchers to quantitatively measure disease progession.
Keywords :
computational complexity; diseases; feature extraction; image classification; image segmentation; medical image processing; optical tomography; Bruch membrane segmentation; age-related macular degeneration patient; computational complexity; discriminative features; disease progession measurement; drusen location detection; drusen position classification; intraretinal cell layer segmentation; optical coherence tomography data; pathological dataset segmentation; quantitative analysis; random forest; retinal pigment epithelium; Accuracy; Image segmentation; Observers; Pathology; Retina; Training; Vegetation;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4