scholarly journals Evans blue staining to detect deep blood vessels in peripheral retina for observing retinal pathology in early-stage diabetic rats

2021 ◽  
Vol 14 (10) ◽  
pp. 1501-1507
Author(s):  
Kang-Pei Shi ◽  
◽  
Chuang-Xin Huang ◽  
Chu-Sheng Cai ◽  
Yan-Jie Zhu ◽  
...  
Keyword(s):  
Blood Vessels ◽  
Evans Blue ◽  
Early Stage ◽  
Diabetic Rats ◽  
Vascular Leakage ◽  
Blue Staining ◽  
Peripheral Retina ◽  
Pathological Changes ◽  
Retinal Blood Vessels ◽  
Leakage Area

AIM: To observe and compare the statistical significance of superficial and deep vascular leakage in the pathological changes of the diabetic rats retina after the Evans blue (EB) perfusion, and utilize the modified whole-retina spreading method to make the slides while protecting the periphery of the retina. METHODS: The Sprague-Dawley (SD) rats were randomly divided into 6 groups. Each group named as the normal groups for 4, 8, and 12wk and the diabetic groups for 4, 8, and 12wk. The EB was injected into the cardiovascular system of the rats at the different time points. The retina of each group was obtained for observation. RESULTS: The superficial vascular leakage was found in all 6 groups. The size of leakage area of superficial retinal blood vessels was (0.54±0.23)%, (0.65±0.11)%, and (0.58±0.10)% in normal group. No notable leakage was found in the deep blood vessels [(0.03±0.04)%, (0.03±0.05)%, and (0.03±0.05)%]. The deep retinal vascular leakage was found in the peripheral retina of diabetic rats. The size of leakage area of superficial retinal blood vessels in diabetic group were (0.53±0.22)%, (0.69±0.16)%, and (0.52±0.11)%. The leakage areas of deep blood vessels were (0.54±0.50)%, (1.42±0.16)%, and (1.80±0.07)% at 4, 8, and 12wk, respectively. There was a statistically difference of the leakage area between the 8th week and the 4th week of diabetes group (P=0.003). The statistically significant difference between the diabetes and the control groups was noted at 4wk and 8wk (P<0.001). CONCLUSION: The main retinal pathological changes of early-stage diabetic rats are the vascular leakage of the periphery of deep retina. Diabetic rats modeled after 8wk have semi-quantitative statistical difference compared with the normal rats, thus early intervention treatment research can start at this time point.

Non-Compactness Attribute Filtering to Extract Retinal Blood Vessels in Fundus Images

2010 ◽  
Vol 1 (3) ◽  
pp. 16-27 ◽  
Author(s):  
I. K. E. Purnama ◽  
K. Y. E. Aryanto ◽  
M. H. F. Wilkinson
Keyword(s):  
Diabetic Retinopathy ◽  
Blood Vessels ◽  
Human Vision ◽  
Retinal Images ◽  
Retinal Vessels ◽  
Fundus Images ◽  
Pathological Changes ◽  
Retinal Blood Vessels ◽  
Average Accuracy ◽  
Filtering Approach

Retinal blood vessels can give information about abnormalities or disease by examining its pathological changes. One abnormality is diabetic retinopathy, characterized by a disorder of retinal blood vessels resulting from diabetes mellitus. Currently, diabetic retinopathy is one of the major causes of human vision abnormalities and blindness. Hence, early detection can lead to proper treatment, and segmentation of the abnormality provides a map of retinal vessels that can facilitate the assessment of the characteristics of these vessels. In this paper, the authors propose a new method, consisting of a sequence of procedures, to segment blood vessels in a retinal image. In the method, attribute filtering with a so-called Max-Tree is used to represent the image based on its gray value. The filtering process is done using the branches filtering approach in which the tree branches are selected based on the non-compactness of the nodes. The selection is started from the leaves. This experiment was performed on 40 retinal images, and utilized the manual segmentation created by an observer to validate the results. The proposed method can deliver an average accuracy of 94.21%.

scholarly journals Early Events inPopulusHybrid andFagus sylvaticaLeaves Exposed to Ozone

2010 ◽  
Vol 10 ◽  
pp. 512-527 ◽  
Author(s):  
R. Desotgiu ◽  
F. Bussotti ◽  
F. Faoro ◽  
M. Iriti ◽  
G. Agati ◽  
...  
Keyword(s):  
Phenolic Compounds ◽  
Evans Blue ◽  
Early Stage ◽  
Blue Staining ◽  
Plant Responses ◽  
Specific Response ◽  
Fast Kinetics ◽  
Quantitative Analyses ◽  
Species Specific ◽  
Fluorescence Transients

This paper aims to investigate early responses to ozone in leaves ofFagus sylvatica(beech) andPopulus maximowicziixPopulus berolinensis(poplar). The experimental setup consisted of four open-air (OA) plots, four charcoal-filtered (CF) open-top chambers (OTCs), and four nonfiltered (NF) OTCs. Qualitative and quantitative analyses were carried out on nonsymptomatic (CF) and symptomatic (NF and OA) leaves of both species. Qualitative analyses were performed applying microscopic techniques: Evans blue staining for detection of cell viability, CeCl3staining of transmission electron microscope (TEM) samples to detect the accumulation of H2O2, and multispectral fluorescence microimaging and microspectrofluorometry to investigate the accumulation of fluorescent phenolic compounds in the walls of the damaged cells. Quantitative analyses consisted of the analysis of the chlorophyll a fluorescence transients (fast kinetics). The early responses to ozone were demonstrated by the Evans blue and CeCl3staining techniques that provided evidence of plant responses in both species 1 month before foliar symptoms became visible. The fluorescence transients analysis, too, demonstrated the breakdown of the oxygen evolving system and the inactivation of the end receptors of electrons at a very early stage, both in poplar and in beech. The accumulation of phenolic compounds in the cell walls, on the other hand, was a species-specific response detected in poplar, but not in beech. Evans blue and CeCl3staining, as well as the multispectral fluorescence microimaging and microspectrofluorometry, can be used to support the field diagnosis of ozone injury, whereas the fast kinetics of chlorophyll fluorescence provides evidence of early physiological responses.

Non-Compactness Attribute Filtering to Extract Retinal Blood Vessels in Fundus Images

2012 ◽  
pp. 208-218
Author(s):  
I. K. E. Purnama ◽  
K. Y. E. Aryanto ◽  
M. H. F. Wilkinson
Keyword(s):  
Diabetic Retinopathy ◽  
Blood Vessels ◽  
Human Vision ◽  
Retinal Images ◽  
Retinal Vessels ◽  
Fundus Images ◽  
Pathological Changes ◽  
Retinal Blood Vessels ◽  
Average Accuracy ◽  
Filtering Approach

Retinal blood vessels can give information about abnormalities or disease by examining its pathological changes. One abnormality is diabetic retinopathy, characterized by a disorder of retinal blood vessels resulting from diabetes mellitus. Currently, diabetic retinopathy is one of the major causes of human vision abnormalities and blindness. Hence, early detection can lead to proper treatment, and segmentation of the abnormality provides a map of retinal vessels that can facilitate the assessment of the characteristics of these vessels. In this paper, the authors propose a new method, consisting of a sequence of procedures, to segment blood vessels in a retinal image. In the method, attribute filtering with a so-called Max-Tree is used to represent the image based on its gray value. The filtering process is done using the branches filtering approach in which the tree branches are selected based on the non-compactness of the nodes. The selection is started from the leaves. This experiment was performed on 40 retinal images, and utilized the manual segmentation created by an observer to validate the results. The proposed method can deliver an average accuracy of 94.21%.

Segmentasi Citra Pembuluh Darah Retina Menggunakan Metode Deteksi Garis Multi Skala

2017 ◽  
Vol 15 (1) ◽  
pp. 13
Author(s):  
Bambang Krismono Triwijoyo
Keyword(s):  
Blood Vessels ◽  
Preventive Measures ◽  
Detection System ◽  
Early Stage ◽  
High Accuracy ◽  
Test Results ◽  
Crucial Step ◽  
Retinal Image Analysis ◽  
Retinal Blood Vessels ◽  
Measurement Results

Changes in retinal blood vessels feature a sign of serious illnesses such as heart disease and stroke. Therefore, the analysis of retinal vascular features can help in detecting these changes and allow patients to take preventive measures at an early stage of this disease. Automation of this process will help reduce the costs associated with the specialist and eliminate inconsistencies that occur in manual detection system. Among the retinal image analysis, image extraction retinal blood vessels is a crucial step before measurement. In this paper, we use an effective methodof automatically extracting the blood vessels of the color images of the retina using a length detector line in several different scales, in order to maintain the strength and eliminates the weaknesses of each detector individual lines, the result of the detection lines on various scales combined to produce a segmentation of each image of the retina. The performance of the method is evaluated quantitatively using DRIVE dataset. Test results show that this method achieve high accuracy is 0.9407 approaching measurement results manually by experts, and this method produces accurate segmentation in detecting retinal blood vessels with effiiency by quickly segmenting time is 2.5 seconds per image.

scholarly journals Mechanisms underlying dysfunction of retinal blood vessels in diabetic rats

2015 ◽  
Vol 145 (2) ◽  
pp. 70-73
Author(s):  
Asami Mori ◽  
Kenji Sakamoto ◽  
Tsutomu Nakahara ◽  
Kunio Ishii
Keyword(s):  
Blood Vessels ◽  
Diabetic Rats ◽  
Retinal Blood Vessels

β-Adrenoceptor-mediated vasodilation of retinal blood vessels is reduced in streptozotocin-induced diabetic rats

2008 ◽  
Vol 49 (2-3) ◽  
pp. 77-83 ◽  
Author(s):  
Taisuke Nakazawa ◽  
Ayumi Sato ◽  
Asami Mori ◽  
Maki Saito ◽  
Kenji Sakamoto ◽  
...  
Keyword(s):  
Blood Vessels ◽  
Diabetic Rats ◽  
Retinal Blood Vessels

scholarly journals Evans Blue Staining Reveals Vascular Leakage Associated with Focal Areas of Host-Parasite Interaction in Brains of Pigs Infected with Taenia solium

PLoS ONE ◽  
2014 ◽  
Vol 9 (6) ◽  
pp. e97321 ◽  
Author(s):  
Miguel Marzal ◽  
Cristina Guerra-Giraldez ◽  
Adriana Paredes ◽  
Carla Cangalaya ◽  
Andrea Rivera ◽  
...  
Keyword(s):  
Evans Blue ◽  
Taenia Solium ◽  
Vascular Leakage ◽  
Blue Staining ◽  
Host Parasite

Review of Various Tasks Performed in the Preprocessing Phase of a Diabetic Retinopathy Diagnosis System

2020 ◽  
Vol 16 (4) ◽  
pp. 397-426
Author(s):  
Muhammad Nadeem Ashraf ◽  
Muhammad Hussain ◽  
Zulfiqar Habib
Keyword(s):  
Diabetic Retinopathy ◽  
Blood Vessels ◽  
Early Stage ◽  
Spherical Shape ◽  
Cost Effective ◽  
Lesion Detection ◽  
Diabetic Patients ◽  
Cad System ◽  
Non Invasive ◽  
Optic Discs

Diabetic Retinopathy (DR) is a major cause of blindness in diabetic patients. The increasing population of diabetic patients and difficulty to diagnose it at an early stage are limiting the screening capabilities of manual diagnosis by ophthalmologists. Color fundus images are widely used to detect DR lesions due to their comfortable, cost-effective and non-invasive acquisition procedure. Computer Aided Diagnosis (CAD) of DR based on these images can assist ophthalmologists and help in saving many sight years of diabetic patients. In a CAD system, preprocessing is a crucial phase, which significantly affects its performance. Commonly used preprocessing operations are the enhancement of poor contrast, balancing the illumination imbalance due to the spherical shape of a retina, noise reduction, image resizing to support multi-resolution, color normalization, extraction of a field of view (FOV), etc. Also, the presence of blood vessels and optic discs makes the lesion detection more challenging because these two artifacts exhibit specific attributes, which are similar to those of DR lesions. Preprocessing operations can be broadly divided into three categories: 1) fixing the native defects, 2) segmentation of blood vessels, and 3) localization and segmentation of optic discs. This paper presents a review of the state-of-the-art preprocessing techniques related to three categories of operations, highlighting their significant aspects and limitations. The survey is concluded with the most effective preprocessing methods, which have been shown to improve the accuracy and efficiency of the CAD systems.

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