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Proceedings Paper

Quantification of retinal lesions by polarization sensitive optical coherence tomography
Author(s): Christoph K. Hitzenberger; Bernhard Baumann; Erich Götzinger; Michael Pircher; Harald Sattmann; Christian Ahlers; Christopher Schütze; Ferdinand Schlanitz; Ursula Schmidt-Erfurth
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Paper Abstract

Segmentation of retinal structures is an important step for quantitative diagnostic applications of optical coherence tomography (OCT) in ophthalmology. Contrary to previous segmentation algorithms that are based on intensity images, we use the tissue specific contrast provided by polarization sensitive (PS) OCT for segmentation of retinal layers and lesions. Our algorithms exploit the polarization scrambling property of the retinal pigment epithelium (RPE) in a first step to segment the RPE. The RPE is then used as a "backbone" to identify further structures like the normal RPE position (indicating Bruch's membrane) or the posterior tips of the photoreceptors. In a final step, lesions like drusen, RPE atrophies, and subretinal fluids are segmented.

Paper Details

Date Published: 2 March 2010
PDF: 4 pages
Proc. SPIE 7550, Ophthalmic Technologies XX, 75500R (2 March 2010); doi: 10.1117/12.840651
Show Author Affiliations
Christoph K. Hitzenberger, Medizinische Univ. Wien (Austria)
Bernhard Baumann, Medizinische Univ. Wien (Austria)
Erich Götzinger, Medizinische Univ. Wien (Austria)
Michael Pircher, Medizinische Univ. Wien (Austria)
Harald Sattmann, Medizinische Univ. Wien (Austria)
Christian Ahlers, Allgemeines Krankenhaus der Stadt Wien (Austria)
Medizinische Univ. Wien (Austria)
Christopher Schütze, Allgemeines Krankenhaus der Stadt Wien (Austria)
Medizinische Univ. Wien (Austria)
Ferdinand Schlanitz, Allgemeines Krankenhaus der Stadt Wien (Austria)
Medizinische Univ. Wien (Austria)
Ursula Schmidt-Erfurth, Allgemeines Krankenhaus der Stadt Wien (Austria)
Medizinische Univ. Wien (Austria)


Published in SPIE Proceedings Vol. 7550:
Ophthalmic Technologies XX
Fabrice Manns; Per G. Söderberg; Arthur Ho, Editor(s)

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