DISPLACEMENT CORRECTION AND SURFACE RECONSTRUCTION OF THE RETINA USING SCANNING LASER OPHTHALMOSCOPIC IMAGES

Citation
Kh. Englmeier et al., DISPLACEMENT CORRECTION AND SURFACE RECONSTRUCTION OF THE RETINA USING SCANNING LASER OPHTHALMOSCOPIC IMAGES, International journal of bio-medical computing, 42(3), 1996, pp. 191-204
Citations number
11
Categorie Soggetti
Mathematical Methods, Biology & Medicine","Engineering, Biomedical","Computer Science Interdisciplinary Applications","Computer Science Theory & Methods","Medical Informatics
ISSN journal
00207101
Volume
42
Issue
3
Year of publication
1996
Pages
191 - 204
Database
ISI
SICI code
0020-7101(1996)42:3<191:DCASRO>2.0.ZU;2-U
Abstract
A method for a three-dimensional surface reconstruction of the retina in the area of the papilla is presented. The surface reconstruction is based on a sequence of discrete gray-level images of the retina recor ded by a scanning laser ophthalmoscope (SLO). The underlying assumptio n of the surface reconstruction algorithm developed here is that the d epth information is also encoded in the brightness values of the singl e pixels in addition to the ordinary spatial 2D information. The brigh tness of an image position depends on the degree of reflection of a co nfocal laser beam. Only those surface structures located directly in t he focus plane of the confocal laser beam produce a high response to t he laser light. The displacements between the single images of a seque nce are considered to be approximately linear and are corrected by app lying the cepstrum technique. The depth is estimated from the volumetr ic representation of the image sequence by searching for the maximal v alue of the brightness within a computed depth profile, at every image position. In the resulting images, disturbances occurring during the recording cause incorrect local estimations of the depth. These local disturbances are corrected by applying specially developed surface imp rovement processes. The work is concluded with a comparison of several different approaches to reduce the noise and disturbances in SLO imag e data.