Improvement of thin retinal vessel extraction using mean matting method

Abstract

In this paper, a new mean matting method based on mean correlation is proposed to extract thin blood vessels precisely. The proposed algorithm is the combination of both supervised and unsupervised method. The supervised methodology performs well in extracting thick blood vessels; however, thin vessels are not precisely extracted. Even the capability of unsupervised method is better in extracting thin vessels; it has some artifacts in the output. The proposed method combines the advantages of both supervised and unsupervised method to extract vessel regions more precisely irrespective of their thickness.Using supervised methodology, thick blood vessels are extracted by training the classifier with the significant features describing the vessel regions. Trimap is generated on the unsupervised output and mean correlation is computed for all unknown pixels in the trimap to classify those pixels into vessels or background. The proposed matting method has less computational complexity compared to other existing matting methods. The performance of the proposed method is evaluated in detail on DRIVE and STARE datasets.

Width measurement of retinal vessels using cubic spline fitting and extended edge‐searching mode

“…1 Some diseases, such as hypertension, diabetes, and atherosclerosis, can generate abnormal changes in the width of retinal blood vessels, 2,3 leading vessels to thicken or narrow in some way or to undergo other morphological changes. [4][5][6] Accurate measurement of vessel width can help doctors make precise judgments about the disease. However, because fundus images are sometimes uneven in luminance and retinal vessels are so tiny and complex in structure that it is difficult to be distinguished with naked eyes, manual measurement of the vessel width requires heavy workload and is time-consuming and inefficient.…”

“…Retinal images provide valuable information for the diagnosis of ophthalmic diseases 1 . Some diseases, such as hypertension, diabetes, and atherosclerosis, can generate abnormal changes in the width of retinal blood vessels, 2,3 leading vessels to thicken or narrow in some way or to undergo other morphological changes 4–6 . Accurate measurement of vessel width can help doctors make precise judgments about the disease.…”