Robust Retinal Vessel Segmentation from a Data Augmentation Perspective

Automatic Retinal Vessel Segmentation

Diabetic Retinopathy is the most common cause of blindness in the working population of the western world and is very common among people who suffer from diabetes. Fortunately, during a clinical examination an ophthalmologist is able to determine the onset of the disease by taking certain features of the retinal vessels of the fundus into account. These features include the narrowing of vessels...

Blood Vessel Segmentation from Retinal Images

Robust Retinal Blood Vessel Segmentation Based on Reinforcement Local Descriptions

Retinal blood vessels segmentation plays an important role for retinal image analysis. In this paper, we propose robust retinal blood vessel segmentation method based on reinforcement local descriptions. A novel line set based feature is firstly developed to capture local shape information of vessels by employing the length prior of vessels, which is robust to intensity variety. After that, loc...

A Relative Study on Retinal Vessel Segmentation

Retinal image processing is a standard medical repetition and offers number of profitable products for physicians. In the field of retinal image processing retinal vessel segmentation is the crucial task for detection of cardiovascular diseases in advance. The recognition of erroneous blood vessel may cause in incorrect clinical diagnosis. Various processing steps are required for the extractio...

Retinal vessel segmentation using multi-scale textons derived from keypoints

This paper presents a retinal vessel segmentation algorithm which uses a texton dictionary to classify vessel/non-vessel pixels. However, in contrast to previous work where filter parameters are learnt from manually labelled image pixels our filter parameters are derived from a smaller set of image features that we call keypoints. A Gabor filter bank, parameterised empirically by ROC analysis, ...