BW - Eye Ophthalmologic decision support system based on clinical workflow and data mining techniques-image registration algorithm
This work addresses a domain-specific problem for ophthalmologists by developing a decision support system, but it is incremental as it builds on existing image registration techniques without achieving full functionality.
The paper tackled the problem of registering ophthalmology images (angiography, color retinography, redfree retinography) by implementing an algorithm based on detecting retinal vascular bifurcation points, using mutual information maximization and Euclidean distance minimization for initial correspondences, with RANSAC for final matching, but did not achieve a fully functional algorithm, only providing analysis for future improvements.
Blueworks - Medical Expert Diagnosis is developing an application, BWEye, to be used as an ophthalmology consultation decision support system. The implementation of this application involves several different tasks and one of them is the implementation of an ophthalmology images registration algorithm. The work reported in this document is related with the implementation of an algorithm to register images of angiography, colour retinography and redfree retinography. The implementations described were developed in the software MATLAB. The implemented algorithm is based in the detection of the bifurcation points (y-features) of the vascular structures of the retina that usually are visible in the referred type of images. There are proposed two approaches to establish an initial set of features correspondences. The first approach is based in the maximization of the mutual information of the bifurcation regions of the features of images. The second approach is based in the characterization of each bifurcation point and in the minimization of the Euclidean distance between the descriptions of the features of the images in the descriptors space. The final set of the matching features for a pair of images is defined through the application of the RANSAC algorithm. Although, it was not achieved the implementation of a full functional algorithm, there were made several analysis that can be important to future improvement of the current implementation.