Konferenční příspěvek

Niemann H., Chrastek R. et al.

Pattern Recognition and Image Analysis: Advances in Mathematical Theory and Applications

MAIK Nauka/Interperiodica Publishing

St. Petersburg, Russian Federation

2005

273 - 276

1054-6618

Ing. Libor Kubečka (FEKT VUT Brno)

Kubecka_PRIA2 [file]

In this paper we address automatic segmentation of the optic nerve head (ONH) with the long-term goal of automatic diagnosis of the early stages of glaucoma. The images discussed are average images obtained from a scanning laser ophthalmoscope (SLO). The segmentation consists of the following main steps: finding a region of interest containing the ONH, constraining the search space for final segmentation, and computing the fine segmentation by an active contour model. The agreement of “true positive pixels,” i.e., pixels attributed to the ONH by both manual and automatic segmentation, is very good. The classification results obtained from three different classifiers using manual or automatic segmentation still reveal the superiority of manual segmentation. One means to further improve automatic segmentation is to use information from an SLO as well as from a fundus camera.