scholarly journals An Automatic Hybrid Method for Retinal Blood Vessel Extraction

2008 ◽  
Vol 18 (3) ◽  
pp. 399-407 ◽  
Author(s):  
Yong Yang ◽  
Shuying Huang ◽  
Nini Rao
Keyword(s):  
Blood Vessel ◽  
Blood Vessels ◽  
Fuzzy Clustering ◽  
Hybrid Method ◽  
Clustering Algorithm ◽  
Retinal Images ◽  
Purification Procedure ◽  
Retinal Blood Vessel ◽  
Fuzzy Clustering Algorithm ◽  
Vessel Extraction

An Automatic Hybrid Method for Retinal Blood Vessel ExtractionThe extraction of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. This paper presents a novel hybrid automatic approach for the extraction of retinal image vessels. The method consists in the application of mathematical morphology and a fuzzy clustering algorithm followed by a purification procedure. In mathematical morphology, the retinal image is smoothed and strengthened so that the blood vessels are enhanced and the background information is suppressed. The fuzzy clustering algorithm is then employed to the previous enhanced image for segmentation. After the fuzzy segmentation, a purification procedure is used to reduce the weak edges and noise, and the final results of the blood vessels are consequently achieved. The performance of the proposed method is compared with some existing segmentation methods and hand-labeled segmentations. The approach has been tested on a series of retinal images, and experimental results show that our technique is promising and effective.

scholarly journals Analysis of Glomerular Filtration Rate in Ischemic Cerebrovascular Diseases under the Magnetic Resonance Angiography Image Segmentation Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yong Ding ◽  
Yuebin Liu ◽  
Cong Peng ◽  
Huanmei Wang ◽  
Yuqin Xu ◽  
...  
Keyword(s):  
Blood Vessel ◽  
Fuzzy Clustering ◽  
Clustering Algorithm ◽  
Vessel Segmentation ◽  
Segmentation Algorithm ◽  
Arterial Stenosis ◽  
Blood Vessel Segmentation ◽  
Fuzzy Clustering Algorithm ◽  
Vessel Stenosis ◽  
Cv Model

In order to discuss the segmentation effect of the magnetic resonance angiography (MRA) image segmentation algorithm based on the fuzzy clustering algorithm and DR-CV model and the prognostic value of glomerular filtration rate (GFR) in the ischemic cerebrovascular disease (ICVD), a total of 178 patients who were admitted to the hospital and received MRA due to ICVD were selected as the research objects of this study. Blood vessel segmentation was performed on the MRA image by fuzzy clustering algorithm and DR-CV model, and all patients were divided into a control group (group A), a single-vessel stenosis group (group B), a two-vessel stenosis group (group C), and a multiple-vessel stenosis group (group D). The GFR was estimated by using the dietary modification equation for kidney disease, and the correlation between GFR and the severity of arterial stenosis in patients with ICVD was analyzed. It was found that the results of the Dice similarity index (DSI) of the MRA image blood vessel segmentation algorithm based on the fuzzy clustering algorithm and the integrated model of boundary and regional information (DR-CV model) were all above 85%. The age and GFR values of the four groups of patients were significantly different ( P  < 0.05). The proportions of patients in groups C and D in the group with low DFR were significantly different from those in groups A and B ( P  < 0.01); the proportions of patients in groups A and B in the high-level GFR group had extremely significant differences compared with group D ( P  < 0.01). Age, GFR, total cholesterol (TC), and high-density lipoprotein-C (HDL-C) were correlated with the degree of arterial stenosis ( P  < 0.05). It showed that the segmentation effect of MRA image blood vessel segmentation algorithm based on the fuzzy clustering algorithm and DR-CV model was better, and the GFR level can be used as an independent risk factor for the ICVD.

Analogizing the Thinning Algorithm and Elicitation of Vascular Landmark in Retinal Images

2016 ◽  
Vol 10 (3) ◽  
pp. 29-37
Author(s):  
Shiny Priyadarshini J. ◽  
Gladis D.
Keyword(s):  
Feature Extraction ◽  
Blood Vessel ◽  
Blood Vessels ◽  
Personal Identification ◽  
Retinal Images ◽  
Feature Points ◽  
Retinal Blood Vessel ◽  
Thinning Algorithm ◽  
Retinal Tissue ◽  
Unique Identity

The retinal tissue is composed of network of blood vessels forming a unique biometric pattern. Feature extraction in retinal blood vessel is becoming an emerging trend in the field of personal identification. Because of its unique identity and less vulnerability to noise and distortion it has become one of the most secured biometric identities. The paper highlights the segmentation of blood vessel and the extraction of feature points such as termination and bifurcation points using Zhang Suen's thinning algorithm in retinal images. A comparison has been made and results are analyzed and tabulated between Zhang Suen and Morphological thinning. The count has been taken for both termination and bifurcation markings as spurious and non- spurious minutiae. The spurious minutiae are removed by using the crossing number method. The results clearly depict that the Zhang Suen's thinning algorithm gives better result when compared to morphological thinning.

scholarly journals Analogizing the Thinning Algorithm and Elicitation of Vascular Landmark in Retinal Images

Ophthalmology ◽  
2018 ◽  
pp. 69-77
Author(s):  
Shiny Priyadarshini J. ◽  
Gladis D.
Keyword(s):  
Feature Extraction ◽  
Blood Vessel ◽  
Blood Vessels ◽  
Personal Identification ◽  
Retinal Images ◽  
Feature Points ◽  
Retinal Blood Vessel ◽  
Thinning Algorithm ◽  
Retinal Tissue ◽  
Unique Identity

The retinal tissue is composed of network of blood vessels forming a unique biometric pattern. Feature extraction in retinal blood vessel is becoming an emerging trend in the field of personal identification. Because of its unique identity and less vulnerability to noise and distortion it has become one of the most secured biometric identities. The paper highlights the segmentation of blood vessel and the extraction of feature points such as termination and bifurcation points using Zhang Suen's thinning algorithm in retinal images. A comparison has been made and results are analyzed and tabulated between Zhang Suen and Morphological thinning. The count has been taken for both termination and bifurcation markings as spurious and non- spurious minutiae. The spurious minutiae are removed by using the crossing number method. The results clearly depict that the Zhang Suen's thinning algorithm gives better result when compared to morphological thinning.

scholarly journals A Study of Retinal Blood Vessel Extraction from the Retinal Images

IJARCCE ◽  
2015 ◽  
Vol 4 (4) ◽  
pp. 509-511 ◽  
Author(s):  
Sandeep Singh ◽  
Dr. Dinesh Kumar
Keyword(s):  
Blood Vessel ◽  
Retinal Images ◽  
Retinal Blood Vessel ◽  
Vessel Extraction

Retinal Blood Vessel Extraction Using a New Enhancement Technique of Modified Convolution Filters and Sauvola Thresholding

2021 ◽  
Author(s):  
Erwin ◽  
Hadrians Kesuma Putra ◽  
Bambang Suprihatin ◽  
Fathoni
Keyword(s):  
Blood Vessel ◽  
Blood Vessels ◽  
Retinal Image ◽  
Histogram Equalization ◽  
Retinal Blood Vessel ◽  
Retinal Blood Vessels ◽  
Convolution Filter ◽  
Image Improvement ◽  
Vessel Extraction ◽  
Convolution Filters

The retinal blood vessels in humans are major components with different shapes and sizes. The extraction of the blood vessels from the retina is an important step to identify the type or nature of the pattern of the diseases in the retina. Furthermore, the retinal blood vessel was also used for diagnosis, detection, and classification. The most recent solution in this topic is to enable retinal image improvement or enhancement by a convolution filter and Sauvola threshold. In image enhancement, gamma correction is applied before filtering the retinal fundus. After that, the image should be transformed to a gray channel to enhance pictorial clarity using contrast-limited histogram equalization. For filter, this paper combines two convolution filters, namely sharpen and smooth filters. The Sauvola threshold, the morphology, and the medium filter are applied to extract blood vessels from the retinal image. This paper uses DRIVE and STARE datasets. The accuracies of the proposed method are 95.37% for DRIVE with a runtime of 1.77[Formula: see text]s and 95.17% for STARE with 2.05[Formula: see text]s runtime. Based on the result, it concludes that the proposed method is good enough to achieve average calculation parameters of a low time quality, quick, and significant.

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