Parallel Multiscale Feature Extraction and Region Growing: Application in Retinal Blood Vessel Detection

This paper presents a parallel implementation based on insight segmentation and registration toolkit for a multiscale feature extraction and region growing algorithm, applied to retinal blood vessels segmentation. This implementation is capable of achieving an accuracy (Ac) comparable to its serial counterpart ( about 92%), but 8 to 10 times faster. In this paper, the Ac of this parallel implementation is evaluated by comparison with expert manual segmentation ( obtained from public databases). On the other hand, its performance is compared with previous published serial implementations. Both these characteristics make this parallel implementation feasible for the analysis of a larger amount of high-resolution retinal images, achieving a faster and high-quality segmentation of retinal blood vessels.