This paper presents a comprehensive review of retinal blood vessel segmentation based on deep learning. The geometric characteristics vessels reflect the health status patients and help to diagnose some diseases such as diabetes hypertension. accurate diagnosis timing treatment these can prevent global blindness patients. Recently, learning algorithms have been rapidly applied due their higher ...

In this paper, we present a novel graph-based method for segmenting the whole 3D vessel tree structures. Our method exploits a new adaptive cylinder flux (ACF) based connectivity framework, which is formulated based on random walks. To avoid the shrinking problem of elongated structure, all existing graph-based energy optimization methods for vessel segmentation rely on skeleton or ROI extracti...

We propose a region growing vessel segmentation algorithm based on spectrum information. First, the algorithm does Fourier transform on the region of interest containing vascular structures to obtain its spectrum information, according to which its primary feature direction will be extracted. Then combined edge information with primary feature direction computes the vascular structure's center ...

This paper presents a novel region-based snake method for vessel segmentation. According to geometric shape analysis of the vessel structure with different scale, an efficient statistical estimation of vessel branches is introduced into the energy objective function, which applies not only the vessel intensity information, but also geometric information of line-like structure in the image. The ...

This paper presents a retinal vessel segmentation method that is inspired by the human visual system and uses a Gabor filter bank. Machine learning is used to optimize the filter parameters for retinal vessel extraction. The filter responses are represented as textons and this allows the corresponding membership functions to be used as the framework for learning vessel and non-vessel classes. T...

Coronary heart disease has been one of the main threats to human health. Coronary angiography is taken as the gold standard for the assessment of coronary artery disease. However, sometimes the images are difficult to visually interpret because of the crossing and overlapping of vessels in the angiogram. Also due to the low contrast of the image between the backdrop and the small blood vessels,...

Segmentation of cerebral blood vessels is of great importance in diagnostic and clinical applications, especially for embolization of cerebral aneurysms and arteriovenous malformations (AVMs). In order to perform embolization of the AVM, the structural and geometric information of blood vessels from 3D images is of utmost importance. For this reason, the in-depth segmentation of cerebral blood ...

We propose a variational approach which combines automatic segmentation and medial structure extraction in a single computationally efficient algorithm. In this paper, we apply our approach to the analysis of vessels in 2D X-ray angiography and 3D X-ray rotational angiography of the brain. Other variational methods proposed in the literature encode the medial structure of vessel trees as a skel...