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AUTOMATIC DELINEATION OF MACULAR REGIONS BASED ON A LOCALLY DEFINED CONTRAST FUNCTION

Citation Author(s):
Rittwik Adhikari, Yogish Kamath, Rajani Jampala, Chandra Sekhar Seelamantula
Submitted by:
J. R HARISH KUMAR
Last updated:
13 September 2017 - 6:51am
Document Type:
Presentation Slides
Document Year:
2017
Event:
Presenters:
HARISH KUMAR J. R.
Paper Code:
2341
 

We consider the problem of fovea segmentation and develop
a technique for delineation of macular regions based on the
active-disc formalism that we recently introduced. The outlining
problem is posed as one of the optimization of a locally
defined contrast function using gradient-ascent maximization
with respect to the affine transformation parameters
that characterize the active disc. For automatic localization
of the fovea and initialization of the active disc, we
use the directional-derivative-based matched filter. We report
validation results on three publicly available fundus image
databases, amounting to a total of 1370 fundus images for
automatic fovea localization and 370 fundus images for fovea
segmentation and macular regions delineation. The proposed
method results in a fovea localization accuracy of 100%, 92%,
and 99.4%, and an average Dice similarity index of 77.78%,
67.46%, and 76.56% on DRIVE, DIARETDB0, and MESSIDOR
fundus image databases, respectively. We have also
developed an ImageJ plugin and an iOS App based on the
proposed method.

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