Title :
Statistical-Based Tracking Technique for Linear Structures Detection: Application to Vessel Segmentation in Medical Images
Author :
Adel, Mouloud ; Moussaoui, Aicha ; Rasigni, Monique ; Bourennane, Salah ; Hamami, Latifa
Author_Institution :
Inst. FRESNEL, Domaine Univ. de St.-Jerome, Marseille, France
fDate :
6/1/2010 12:00:00 AM
Abstract :
Linear structures such as blood vessels in medical images are important features for computer-aided diagnosis and follow-up of many diseases. In this letter a new tracking-based segmentation method is proposed to detect blood vessels in retinal images. Bayesian segmentation with the Maximum a posteriori (MAP) Probability criterion is used for that purpose. Tests on simulated and retinal images are presented and compared with a vessel detection technique. Our method performs better results.
Keywords :
blood vessels; eye; image segmentation; medical diagnostic computing; object detection; probability; tracking; Bayesian segmentation; blood vessel segmentation; computer-aided diagnosis; linear structures detection; maximum a posteriori probability criterion; medical images; retinal images; statistical-based tracking technique; Edge detection; medical images; retinal vessels; statistical segmentation;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2010.2046697