In this paper we introduce a new deformable model, called eigensnake, for segmentation of elongated structures in a probabilistic framework. Instead of snake attraction by specific image features extracted independently of the snake, our eigensnake learns an optimal object description and searches for such image feature in the target image. This is achieved applying principal component analysis...

This thesis describes a technique for editing segmentation results of vessels, which should enhance usage and reduce work duration for physicians by using a simple and fast way of interaction. Moreover also a quick calculation of an accurate result was of primary interest. Since vascular structures are vulnerable to diseases, vessels are the main focus of this thesis. Nowadays, Image Analysis i...

Retinal fundus images are used in the diagnosis and treatment of many eye conditions, such as diabetic retinopathy and glaucoma. During a clinical examination, an ophthalmologist is able to determine the onset of disease by taking certain features of the retinal vessels of the fundus into account. Often the ophthalmologist will need to select what parts of a retinal fundus image constitute vess...

The risk of cardio vascular diseases can be identified by measuring the retinal blood vessel. The identification of wrong blood vessel may result in wrong clinical diagnosis. This proposed system addresses the problem of identifying the true vessel by vascular structure segmentation. In this proposed model the segmented vascular structure is modelled as a vessel segment graph and the true vesse...

This paper presents a method for airway tree segmentation that uses a combination of a trained airway appearance model, vessel and airway orientation information, and region growing. The method uses a voxel classification based appearance model, which involves the use of a classifier that is trained to differentiate between airway and non-airway voxels. Vessel and airway orientation information...

1. Abstract Laplacian eigenmap is a useful technique to improve clusterbased segmentation of multivariate images. However, this approach requires an excessive amount of computations when processing large image datasets. To that end, we present a GPU-based acceleration procedure for vessel segmentation problems. 2. Laplacian Eigenmap As described in Laskaris et. al. [1], the Laplacian Eigenmap i...

CONTRIBUTIONS We propose a novel framework for joint 3-D vessel segmentation and centerline extraction. The approach is based on multivariate Hough voting and oblique random forests (RFs) that we learn from noisy annotations. It relies on steerable filters for the efficient computation of local image features at different scales and orientations. EXPERIMENTS We validate both the segmentation ...

Accurate segmentation and evaluation of the anatomical and pathological features of retinal vessels are critical for the diagnosis and study of many ocular diseases. These include retinopathy of prematurity (ROP). ROP is a disorder of the retinal blood vessels that is a major cause of vision loss in premature neonates. It is proposed a methodology for extracting the vascular network in the huma...

Segmentation of vessels in biomedical images is important as it can provide insight into analysis of vascular morphology, topology and is required for kinetic analysis of flow velocity and vessel permeability. Intravital microscopy is a powerful tool as it enables in vivo imaging of both vasculature and circulating cells. However, the analysis of vasculature in those images is difficult due to ...