Abstract
Retinal imaging system assists ophthalmologists to diagnose the diseases and to monitor the treatment processes. Conventionally, fundus retinal images are obtained from expensive systems like fluorescein angiography and fundus photography but these systems are large tabletop units and can only be handled by trained technicians. Hence, this study reports a low cost, compact and user friendly smartphone ophthalmoscope to perform indirect ophthalmoscopy. By using this system, initial and periodic screening of retina (both center and periphery regions) becomes easier. Traditionally, retinal diseases are diagnosed by manual observations of fundus images and it is a time consuming process. So, automatic retinal disease diagnosing systems are introduced by extracting the essential features of the fundus retinal images. One of the most essential features of the retina is the blood vessels as its morphological changes helps in diagnosing the retinal diseases. Hence, in this study blood vessels are extracted from smartphone ophthalmoscope (SO) images using level set method to develop an automatic retinal disease diagnosing systems for ophthalmologists. The performance of the retinal vasculature segmentation algorithm is compared and analyzed on DRIVE database of retinal images and on smartphone ophthalmoscope images using the measures like sensitivity, specificity and accuracy level.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Devi, S.S., Ramachandran, K.I., Sharma, A. (2015). Retinal Vasculature Segmentation in Smartphone Ophthalmoscope Images. In: Goh, J., Lim, C. (eds) 7th WACBE World Congress on Bioengineering 2015. IFMBE Proceedings, vol 52. Springer, Cham. https://doi.org/10.1007/978-3-319-19452-3_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-19452-3_18
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19451-6
Online ISBN: 978-3-319-19452-3
eBook Packages: EngineeringEngineering (R0)