Detection of Various Anatomical Structures in Retinal Images and Fovea Detection using Wavelets
Abstract
Detection of anatomical structures is one of the most
important areas in ophthalmology. On day today life everyone are
experiencing more defect on retinal areas this paper is a small
contribution for such cases by detecting different features (like blood
vessels, optic disk, macula, fovea etc.) automatically from retinal
image. This presents simple techniques for extracting blood vessels,
some relevant information on optic disk and also mainly focusing on
fovea region and as a further study top hat transformation is been
compared with the results of bottom hat transformation during
extraction of blood vessels. This is compared with wavelets and
which method gives better result is determined. The experimental
results illustrate the usefulness of the new method. Thus the
proposed scheme is robust also.
Keywords
Full Text:
PDFReferences
http://webvision.med.utah.edu/sretina.html overview.
C. Sinthanayothin, J. F. Boyce, H. L. Cook, and T. H. Williamson,
“Automated localisation of the optic disc, fovea, and retinal blood
vessels from digital color fundus images,” Br. Journal of Opthalmol, vol.
,no. 1, pp. 902–910, 1999.
O. Chutatape, “Fundus foveal localization based on vessel model,” in
Proceedings of the 28th IEEE EMBS Annual International Conference
New York City, USA, 2006, pp. 4440–4444.
“Drive database,” http://www.isi.uu.nl/Research/Databases/DRIVE/.(a)
(b) (c) Fig. 6. Experimental results (a): Fundus color image (b): Blood
vessels, horizontal line and Vertical strip (c) : Macula (blue circular
region) and fovea(red region nearer to the center of the macula)
S. Chaudhuri, S. Chatterjee, N. Katz, M. Nelson, and M. Goldbaum,
“Detection of blood vessels in retinal images using two dimensional
matched filters,” IEEE Transactions on Medical Imaging,vol. 8, no. 3,
pp. 263–269, 1989.
B. Al-Diri, A. Hunter, and D. Steel, “An active contour model for
segmenting and measuring retinal vessels,” IEEE Transactions on
Medical Imaging, vol. 24, no. 9, pp. 1488–1497, 2009.
F. Zana and J.-C. Klein, “Segmentation of vessel-like patterns using
mathematical morphology and curvature evaluation,” IEEE Transactions
on Medical Imaging, vol. 10, no. 7, pp. 1010–1019, 2001.
J. Staal, M. D. Abramoff, M. Niemeijer, M. A.Viergever, and B. van
Ginneken, “Ridge-based vessel segmentation in color images of the
retina,” IEEE Transactions on Medical Imaging, vol. 23,no. 4, pp. 501–
, 2004.
Soumitra Samanta1, Sanjoy Kumar Saha2 and Bhabatosh Chanda1”
ECSU, Indian Statistical Institute, Kolkata, India CSE Department,
Jadavpur University, Kolkata, India “A simple and fast algorithm to
detect the fovea region in fundus of retinal image” 978-0-7695-4329-
/11 $26.00 © 2011 IEEE DOI 10.1109/EAIT.2011.22
M.V.Ibaez and A. Simo, “Bayesian detection of the fovea in eye fundus
angiographies,” Pattern Recognition Letters, vol. 20, pp. 229–240, 1999.
S. Sekhar, W. Al-Nuaimy, and A. K. Nandi,“Automated localization of
optic disk and fovea in retinal fundus images,” in 16th European Signal
Processing Conference (EUSIPCO 2008),Lausanne, Switzerland.
EURASIP, August 25 29,2008
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.