The extraction of vessel centerlines allows for better understanding of their topology, and can be used for further registration or quantification. We present a new method to extract the centerlines from Magnetic Resonance Angiographies. We use the gradient and the eigenvalues of the Hessian matrix to interpolate the zero-crossing of the gradient vector in the cross-sectional directions. Then, ...

In this article, we present the work towards improving the overall workflow of the Percutaneous Coronary Interventions (PCI) procedures by capacitating the imaging instruments to precisely monitor the steps of the procedure. In the long term, such capabilities can be used to optimize the image acquisition to reduce the amount of dose or contrast media employed during the procedure. We present t...

Due to lack of the coverage of 3G/4G network, satellite communication which costs excessively is the main approach used in ocean to provide network service. Ocean mobile delay tolerant network (OMDTN) can provide low-cost data transmission service in the network by utilizing the contact chances of moving vessels. Spatio-temporal contact pattern is one of the key metrics to improve the efficienc...

This paper presents a novel technique to detect ships and estimate their velocities. The technique takes advantage of two existing techniques and inserts some innovation by using the Radon Transform to detect the ship wake and estimate the range velocity component. For detection, cross correlation of split-look is used. To estimate the azimuth velocity component a sequence of single-look SAR im...

Cerebral small vessel disease (SVD) is a common finding on magnetic resonance images of elderly people. White matter lesions (WML) are important markers for not only the small vessel disease, but also neuro-degenerative diseases including multiple sclerosis, Alzheimer’s disease and vascular dementia. Volumetric measurements such as the “total lesion load”, have been studied and related to these...

Deep convolutional neural networks have achieved great results on image classification problems. In this paper, a new method using a deep convolutional neural network for detecting blood vessels in Bmode ultrasound images is presented. Automatic blood vessel detection may be useful in medical applications such as deep venous thrombosis detection, anesthesia guidance and catheter placement. The ...

Retinal blood vessels are important structures in ophthalmological images. Many detection methods are available, but the results are not always satisfactory. In this paper, we present a novel model based method for blood vessel detection in retinal images. It is based on a Laplace and thresholding segmentation step, followed by a classification step to improve performance. The last step assures...

Exudates are one of the primary signs of diabetic retinopathy, which is a main cause of blindness and can be prevented with an early screening process. Diabetic retinopathy eye disease is harmful; causes pressure in eye nerve fibre. It is essential to diagnose it earlier. In this paper we have process on images of retina with the help of Digital Image Processing (DIP) tool in which images are d...

A robust and efficient method for the segmentation of vessel cross-sections in contrast enhanced CT and MR images is presented. The primary innovation of the technique is the boundary propagation by mean shift analysis combined with a smoothness constraint. Consequently, the robustness of the mean shift to noise is enhanced by the use of apriori information on boundary smoothness. This processi...

Diabetic retinopathy eye disease which is harmful; cuases pressure in eye nerve fiber. It is essential to diagnose it earlier. And this paper we have process on images of retina with the help of Digital Image Processing (DIP) tool. Therefore in which images are getting detected and then processed. At last we distinguish the problem of detecting edges in images as a diabetic retinopathy (DR), ma...