Improving the accuracy of optic disc detection by finding maximal weighted clique of multiple candidates of individual detectors

In this paper, we propose a method to improve the automatic detection of the optic disc on fundus images. We have studied and implemented some of the optic disc detectors from concerning literature to organize them into an ensemble system. As a former work, we proposed an ensemble-based optic disc detection system, based on simple majority voting which already outperformed the individual detectors. To improve further the performance of the ensemble-based system, now we examine how we can extract more candidates from the individual algorithms to have the appropriate location of the optic disc among them. We also assign weights to each candidate based on the priority suggested by the algorithms. We consider these weighted candidates as vertices of a graph and look for a subgraph with a maximal sum of weights constrained by the geometry of the optic disc. Experimental results are also presented to see the improvement.