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.
Palomera-Pérez
Miguel A
MA
Department of Computer Systems Engineering and Automatization, Instituto de Investigaciones en Matematicas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Mexico 01600, Mexico. ese.mike@gmail.com
Martinez-Perez
M Elena
ME
Benítez-Pérez
Hector
H
Ortega-Arjona
Jorge Luis
JL
D000465:Algorithms; D016208:Databases, Factual; D003941:Diagnostic Techniques, Ophthalmological; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012160:Retina / Q000033:anatomy & histology*; D012171:Retinal Vessels / Q000033:anatomy & histology*