Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

D. Sheet, S. P. K. Karri, S. Conjeti, S. Ghosh, J. Chatterjee, A. K. Ray
Detection of retinal vessels in fundus images through transfer learning of tissue specific photon interaction statistical physics
Proceedings of International Symposium on Biomedical Imaging (ISBI), San Francisco, CA, USA, April 2013 (bib)

Loss of visual acuity on account of retina-related vision impairment can be partly prevented through periodic screening with fundus color imaging. Largescale screening is currently challenged by inability to exhaustively detect fine blood vessels crucial to disease diagnosis. In this work we present a framework for reliable blood vessel detection in fundus color imaging through inductive transfer learning of photon-tissue interaction statistical physics. The source task estimates photon-tissue interaction as a spatially localized Poisson process of photons sensed by the RGB sensor. The target task identifies vascular and non-vascular tissues using knowledge transferred from source task. The source and target domains are retinal images obtained using a color fundus camera with white-light illumination. In experimental evaluation with the DRIVE database, we achieve the objective of vessel detection with max. avg. accuracy of 0.9766 and kappa of 0.8213.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Edit | Attach | Refresh | Diffs | More | Revision r1.11 - 19 Jul 2016 - 16:26 - NassirNavab

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif