Automatic extraction of blood vessels in the retinal vascular tree using multiscale medialness.

We propose an algorithm for vessel extraction in retinal images. The first step consists of applying anisotropic diffusion filtering in the initial vessel network in order to restore disconnected vessel lines and eliminate noisy lines. In the second step, a multiscale line-tracking procedure allows detecting all vessels having similar dimensions at a chosen scale.

Towards a quantitative in vivo evaluation of venous blood echogenicity: image processing versus subjective assessment.

Purpose: Spontaneous blood echogenicity in vein ultrasound images may be a marker for an increased erythrocyte aggregability, but a reliable quantitative evaluation method is a prerequisite for its use in clinical studies. We compared a simple scoring system of blood echogenicity intensity and pattern, with automatic image analysis.

Material And Methods: 157 femoral and popliteal vein digitized ultrasound sequences were reviewed by two independent observers who chose an image, delimited an area of interest (ROI), and graded blood echogenicity intensity and pattern, using a four class score.