A computational efficient external energy for active contour segmentation using edge propagation

Active contours or snakes are widely used for segmentation and tracking. We propose a new active contour model, which converges reliably even when the initialization is far from the object of interest. The proposed segmentation technique uses an external energy function where the energy slowly decreases in the vicinity of an edge. This new energy function is calculated using an efficient dual scan line algorithm. The proposed energy function is tested on computational speed, its effect on the convergence speed of the active contour and the segmentation result. The proposed method gets similar segmentation results as the gradient vector flow active contours, but the energy function needs much less time to calculate

A ribbon of twins for extracting vessel boundaries

This paper presents an efficient model for automatic detection and extraction of blood vessels in ocular fundus images. The model is formed using a combination of the concept of ribbon snakes and twin snakes. On each edge, the twin concept is introduced by using two snakes, one inside and one outside the boundary. The ribbon concept integrates the pair of twins on the two vessel edges into a single ribbon. The twins maintain the consistency of the vessel width, particularly on very blurred, thin and noisy vessels. The model exhibits excellent performance in extracting the boundaries of vessels, with improved robustness compared to alternative models in the presence of occlusion, poor contrast or noise. Results are presented which demonstrate the performance of the discussed edge extraction method, and show a significant improvement compared to classical snake formulations

REVIEW - A reference data set for retinal vessel profiles

This paper describes REVIEW, a new retinal vessel reference dataset. This dataset includes 16 images with 193 vessel segments, demonstrating a variety of pathologies and vessel types. The vessel edges are marked by three observers using a special drawing tool. The paper also describes the algorithm used to process these segments to produce vessel profiles, against which vessel width measurement algorithms can be assessed. Recommendations are given for use of the dataset in performance assessment. REVIEW can be downloaded from http://ReviewDB.lincoln.ac.uk

Cell nuclei detection using globally optimal active contours with shape prior

Cell nuclei detection in fluorescent microscopic images is an important and time consuming task for a wide range of biological applications. Blur, clutter, bleed through and partial occlusion of nuclei make this a challenging task for automated detection of individual nuclei using image analysis. This paper proposes a novel and robust detection method based on the active contour framework. The method exploits prior knowledge of the nucleus shape in order to better detect individual nuclei. The method is formulated as the optimization of a convex energy function. The proposed method shows accurate detection results even for clusters of nuclei where state of the art methods fail

Atlas-Based Prostate Segmentation Using an Hybrid Registration

Purpose: This paper presents the preliminary results of a semi-automatic method for prostate segmentation of Magnetic Resonance Images (MRI) which aims to be incorporated in a navigation system for prostate brachytherapy. Methods: The method is based on the registration of an anatomical atlas computed from a population of 18 MRI exams onto a patient image. An hybrid registration framework which couples an intensity-based registration with a robust point-matching algorithm is used for both atlas building and atlas registration. Results: The method has been validated on the same dataset that the one used to construct the atlas using the "leave-one-out method". Results gives a mean error of 3.39 mm and a standard deviation of 1.95 mm with respect to expert segmentations. Conclusions: We think that this segmentation tool may be a very valuable help to the clinician for routine quantitative image exploitation.Comment: International Journal of Computer Assisted Radiology and Surgery (2008) 000-99