Measurement of intra-operative cortical brain movement is necessary to drive mechanical models developed to predict sub-cortical shift. At our institution, this is done with a tracked laser range scanner. This device acquires both 3D range data and 2D photographic images. 3D cortical brain movement can be estimated if 2D photographic images acquired over time can be registered. Previously, we h...

Accurate determination of the vessel axis is a prerequisite for automated visualization and quantification of artery diseases. This paper presents an evaluation of different methods for approximating the centerline of the vessel in a phantom simulating the peripheral arteries. Six algorithms were used to determine the centerline of a synthetic peripheral arterial vessel. They are based on: ray ...

Segmentation of retinal blood vessels is significant to diagnosis and evaluation of ocular diseases like glaucoma and systemic diseases such as diabetes and hypertension. The retinal blood vessel segmentation for small and low contrast vessels is still a challenging problem. To solve this problem, a new method based on cake filter is proposed. Firstly, a quadrature filter band called cake filte...

Although retinal vessel segmentation has been extensively researched, a robust and time efficient segmentation method is highly needed. This paper presents a local adaptive thresholding technique based on gray level cooccurrence matrix- (GLCM-) energy information for retinal vessel segmentation. Different thresholds were computed using GLCM-energy information. An experimental evaluation on DRIV...

The blood vessel detection and segmentation technique plays a useful clinical role in an automated retinopathy analysis system. But manual segmentation of vessels requires expertise. It is a very tedious and time consuming task. Employing computational intelligence for this purpose would help in efficient retinal analysis. An user friendly graphical user interface (GUI) that is MATLAB based too...

In this paper presents , segmentation of blood vessels in retinal images based on neural network (NN) scheme of gray-level and moment invariants-based features. In the past, rural based methods are used segment the blood vessels. It has more complexity and less accuracy of blood vessels detection in retinal images. This paper proves better performance in terms of blood vessel detection in stare...

INTRODUCTION Non-invasive quantitative assessment of the cerebral vasculature is of high diagnostic and therapeutic interest. Prerequisite for quantitative description of blood vessels is voxel-wise classification of angiographic data sets into vessel and non-vessel structures. Among the vast of algorithms suitable for vessel segmentation [1, 2] the level-set technique has been established as a...

We present a pulmonary vessel segmentation algorithm, which is fast, fully automatic and robust. It uses a coarse segmentation of the airway tree and a left and right lung labeled volume to restrict a vessel enhancement filter, based on an offset medialness function, to the lungs. We show the application of our algorithm on contrast-enhanced CT images, where we derive a clinical parameter to de...

Artery/Vein (A/V) of retinal vessel is helpful for the automating the detection of various diseases such as Diabetic Retinography, high blood pressure, pancreas, and other vascular conditions. An automated approach is presented in this paper for classification of blood vessels into Artery/Vein based on the features extracted from the centerline pixels. The proposed method consists of 4 importan...

Different approaches of visualization techniques and segmentation methods for computed tomograpy angiography datasets are investigated. The particular characteristics of this data are addressed. A global path-optimisation method for a reliability-enhanced vessel-tracking method was introduced. Furthermore an interactive segmentation technique focusing on the clinical use is proposed.