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Retinal Vascular Branching in Healthy and Diabetic Subjects
摘要： PURPOSE. To measure the effect of nonproliferative diabetic retinopathy (NPDR) on retinal branching. To compare vascular branching in healthy and diabetic subjects with established biophysical models. METHODS. Vascular bifurcations in arteries and veins were imaged in 17 NPDR and 26 healthy subjects with the Indiana adaptive optics scanning laser ophthalmoscope (AOSLO). Vessel measurements were grouped according to parent vessel diameters into large ((cid:2)50 ~ <100 lm) and small ((cid:2)20 ~ <50 lm) sizes. Vessel diameters and bifurcation angles were measured manually. Vascular diameters were compared with predictions of Murray’s law using curve ?tting. For analysis of bifurcation angles, two models from Zamir were compared: one based on the power required for blood pumping, the other based on drag force between blood and vascular wall. RESULTS. For normal larger vessels, the exponent relating the parent and daughter branching diameters was signi?cantly less than the value of 3 predicted by Murray’s law (arteries: 2.59; veins: 1.95). In NPDR, the best-?t exponent was close to 3 for arteries but close to 2 in healthy subjects in veins, (arteries: 3.09; veins: 2.16). For both small arteries and veins, diabetics’ exponent differed from healthy subjects (P < 0.01). Bifurcation angles in the healthy subjects (788 6 with a standard error (SE) of 0.98) were not much different than in NPDR (798 6 SE 1.38). The model based on minimizing pumping power predicted the measurements better than the one minimizing the vascular drag and lumen surface area. CONCLUSIONS. The relation between parent and daughter branch diameters changes in diabetes, but the branching angles do not.
关键词： adaptive optics scanning laser ophthalmoscopy,diabetic retinopathy,vascular branching,Murray’s law
更新于2025-09-10 09:29:36
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Social deprivation as a risk factor for late presentation of proliferative diabetic retinopathy
摘要： Purpose: The aim of this study was to determine whether social deprivation is a risk factor for late presentation of patients with proliferative diabetic retinopathy and whether it affects their access to urgent laser treatment. Methods: Using a 2:1 case: control design, 102 patients referred to a UK teaching hospital as part of the UK Diabetic Retinopathy National Screening Programme were identified for the period between 1 June 2010 to 1 June 2013. Social deprivation was scored using the Index of Multiple Deprivation 2010. Additional variables considered included age, duration of disease, ethnicity, and HbA1c at time of referral. Results: The cases comprised 34 patients referred with proliferative (grade R3) retinopathy with a control group of 68 patients with lower retinopathy grades; two control patients were excluded due to incomplete data. On univariate analysis, R3 retinopathy was associated with higher social deprivation (P,0.001, Mann–Whitney U-test), and with higher HbA1c (11.5% vs 8.4%; P,0.001, Mann–Whitney U-test). Forward stepwise multivariable analysis showed that the association of R3 retinopathy with deprivation was significant even after adjusting for HbA1c (P=0.016). On univariate analysis South Asian ethnicity was also identified as being a risk factor for presentation with R3 retinopathy, but this was no longer significant when HbA1c was adjusted for in a forward stepwise logistic regression analysis. Conclusion: In our cohort social deprivation appears to be associated with late presentation of proliferative diabetic retinopathy. Our study supports the need to target these groups to reduce preventable blindness and to identify strategies which overcome barriers to care.
关键词： social deprivation,diabetes,proliferative diabetic retinopathy,index of multiple deprivation
更新于2025-09-10 09:29:36
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An effective image processing method for detection of diabetic retinopathy diseases from retinal fundus images
摘要： Diabetic retinopathy (i.e., DR), is an eye disorder caused by diabetes, diabetic retinopathy detection is an important task in retinal fundus images due the early detection and treatment can potentially reduce the risk of blindness. Retinal fundus images play an important role through disease diagnosis, disease recognition (i.e., by ophthalmologists), and treatment. The current state-of-the-art techniques are not satisfied with sensitivity and specificity. In fact, there are still other issues to be resolved in state-of-the-art techniques such as performances, accuracy, and easily identify the DR disease effectively. Therefore, this paper proposes an effective image processing method for detection of diabetic retinopathy diseases from retinal fundus images that will satisfy the performance metrics (i.e., sensitivity, specificity, accuracy). The proposed automatic screening system for diabetic retinopathy was conducted in several steps: Pre-processing, optic disc detection and removal, blood vessel segmentation and removal, elimination of fovea, feature extraction (i.e., Micro-aneurysm, retinal hemorrhage, and exudates), feature selection and classification. Finally, a software-based simulation using MATLAB was performed using DIARETDB1 dataset and the obtained results are validated by comparing with expert ophthalmologists. The results of the conducted experiments showed an efficient and effective in sensitivity, specificity and accuracy.
关键词： micro-aneurysms,DIARETDB1,diabetic retinopathy,exudates,retinal hemorrhage
更新于2025-09-10 09:29:36
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[IEEE 2018 37th Chinese Control Conference (CCC) - Wuhan (2018.7.25-2018.7.27)] 2018 37th Chinese Control Conference (CCC) - Computer Aided Diagnosis for Diabetic Retinopathy based on Fundus Image
摘要： Diabetic Retinopathy (DR) is an eye abnormality caused by long term diabetes, which can lead to vision defects or even blindness. Performing retinal screening examinations on all diabetic patients is a hard work due to the limited number of specialists cannot keep up with the increasing prevalence of diabetes, and hence there are many undiagnosed and untreated cases of DR. Computer aided diagnosis (CAD) is a good way to save the patient’s vision and to help the ophthalmologists in mass screening of diabetes sufferers. The main purpose of the proposed study is to design an automated grading approach for DR screening, using a publicly available database of retinal images, which can evaluate the fundus images like human experts while achieving a high sensitivity for the detection of DR. This paper gives a summary of the results obtained by our previous studies. Together with these results and the DR grading schemes, we provide an automatic analysis approach for the risk of macular edema and the retinopathy grade. Experimental results indicate that the performance of our approach on this database is comparable to that of human experts.
关键词： Optic disc,Macula,Diabetic Retinopathy,Pattern Recognition,Exudates
更新于2025-09-10 09:29:36
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A Novel Approach for Diagnosing Diabetic Retinopathy in Fundus Images
摘要： In recent years the medical profession has seen an ever increasing demand for diagnosis and a permanent cure for illnesses caused by climatic-changes, unwholesome food and environmental pollution. Also the appearances of hitherto unknown viral diseases have caused eye diseases, which have prompted surgeons to monitor the health of the eyes. Potential new therapies that may help in preserving sight in the growing population of diabetic patients into the 21st Century. Early detection of diseases affecting the eyes reduces the risk of permanent damage. Some of the serious conditions which warrant early diagnosis are: Glaucoma, floaters, macula degradation and diabetic retinopathy. In the early stages, a choice of treatment options exist, which dwindles as the disease spreads. A visual inspection of the optic disc, macula and the blood vessels of the eye requires to be done routinely. Diabetic patients run the risk of damage to retinal vessels, which are referred to as diabetic retinopathy. This may further be classified as: Non-proliferative diabetic retinopathy and proliferative diabetic retinopathy. In scientific literatures, feature extraction method has been reported for diagnosis and classification. In this study a systematic Decide, Detect, Determine and Do approach for analyzing diabetic retinopathy images has been taken up. The proposed approach gives a clearer picture of the abnormality, its type (NPDR or PDR), its status (viz., mild, moderate or severe) and finally the appropriate treatment.
关键词： Macula,Diabetic Retinopathy,PDR,Blood Vessels,NPDR,Optic Disc
更新于2025-09-10 09:29:36
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[Advances in Intelligent Systems and Computing] Emerging Trends in Expert Applications and Security Volume 841 (Proceedings of ICETEAS 2018) || Exploring Open Source for Machine Learning Problem on Diabetic Retinopathy
摘要： Open-source operating system, as well as its packages, is more powerful and secure than the proprietary sources. In the proprietary source, software source code is not easily available because it is secret; by contrast in the open-source operating system source code is easily available, so any programmer can change the code and implement their ideas and modify it because of its openness. Also, one major advantage is that we do not need to spend a huge amount of money on the software. So, in this paper, we used open-source software for coding purposes and looked at the data available on the UCI machine learning repository on the diabetic retinopathy.
关键词： Neural network,Open-source,Boosted decision tree,Diabetic retinopathy
更新于2025-09-10 09:29:36
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Modified Curvature-based Trigonometric Identities for Retinal Blood Vessel Tortuosity Measurement in Diabetic Retinopathy Fundus Images
摘要： In current clinical practice, there is no specific standard and grading system that can be used to measure the behaviour of the retinal blood vessel curvature. The retinal blood vessel curvature is measured based on clinical experiences. It is very subjective and inconsistent to describe the presence of tortuosity in fundus images. Thus, this paper aims to measure the tortuosity of retinal blood vessel using curvature-based method and investigate its relationship with diabetic retinopathy (DR) disease. The proposed tortuosity measures have been tested on 43 fundus images belonging to patients who have been diagnosed with DR disease and validated by two clinical experts from our collaborative hospital. On average, the proposed algorithm achieved 90.7% (accuracy), 98.72% (sensitivity) and 9.3% (false negative rate), that shows significant tortuosity presence in diabetic retinopathy fundus images.
关键词： Tortuosity,Retinal Blood Vessel,Digital Fundus Images,Diabetic Retinopathy,Curvature-based Method
更新于2025-09-10 09:29:36
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Optical coherence tomography angiography (OCTA) flow speed mapping technology for retinal diseases
摘要： Introduction: Optical coherence tomography angiography (OCTA) is a noninvasive imaging modality for depth-resolved visualization of retinal vasculature. Angiographic data couples with structural data to generate a cube scan, from which en-face images of vasculature can be obtained at various axial positions. OCTA has expanded understanding of retinal vascular disorders and has primarily been used for qualitative analysis. Areas covered: Recent studies have explored the quantitative properties of OCTA, which would allow for objective assessment and follow-up of retinal pathologies. Various quantitative metrics have been developed, such as foveal avascular zone area and vessel density. However, quantitative assessment of the characteristics of retinal blood flow remains limited, as OCTA provides an image depicting either the presence or absence of flow at a particular region without information of relative velocities. The development of variable interscan time analysis (VISTA) overcomes this limitation. The VISTA algorithm generates a color-coded map of relative blood flow speeds. VISTA has already demonstrated utility in furthering our understanding of various retinal pathologies, such as geographic atrophy, choroidal neovascularization, aneurysmal type 1 neovascularization, and diabetic retinopathy. Expert commentary: VISTA, an OCTA flow speed mapping technique, may have a role in developing the utility of OCTA as a screening tool.
关键词： flow speed mapping,diabetic retinopathy,age-related macular degeneration,VISTA,quantitative OCTA,OCTA,Optical coherence tomography angiography,variable interscan time analysis,OCT
更新于2025-09-10 09:29:36
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Evaluation of a deep learning image assessment system for detecting severe retinopathy of prematurity
摘要： background Prior work has demonstrated the near-perfect accuracy of a deep learning retinal image analysis system for diagnosing plus disease in retinopathy of prematurity (ROP). Here we assess the screening potential of this scoring system by determining its ability to detect all components of ROP diagnosis. Methods Clinical examination and fundus photography were performed at seven participating centres. A deep learning system was trained to detect plus disease, generating a quantitative assessment of retinal vascular abnormality (the i-ROP plus score) on a 1–9 scale. Overall ROP disease category was established using a consensus reference standard diagnosis combining clinical and image-based diagnosis. Experts then ranked ordered a second data set of 100 posterior images according to overall ROP severity. results 4861 examinations from 870 infants were analysed. 155 examinations (3%) had a reference standard diagnosis of type 1 ROP. The i-ROP deep learning (DL) vascular severity score had an area under the receiver operating curve of 0.960 for detecting type 1 ROP. Establishing a threshold i-ROP DL score of 3 conferred 94% sensitivity, 79% specificity, 13% positive predictive value and 99.7% negative predictive value for type 1 ROP. There was strong correlation between expert rank ordering of overall ROP severity and the i-ROP DL vascular severity score (Spearman correlation coefficient=0.93; p<0.0001). Conclusion The i-ROP DL system accurately identifies diagnostic categories and overall disease severity in an automated fashion, after being trained only on posterior pole vascular morphology. These data provide proof of concept that a deep learning screening platform could improve objectivity of ROP diagnosis and accessibility of screening.
关键词： retinopathy of prematurity,ROP,deep learning,screening,artificial intelligence
更新于2025-09-10 09:29:36
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Scan, dwell, decide: Strategies for detecting abnormalities in diabetic retinopathy
摘要： Diabetic retinopathy (DR) is a disease which is widely diagnosed using (colour fundus) images. Efficiency and accuracy are critical in diagnosing DR as lack of timely intervention can lead to irreversible visual impairment. In this paper, we examine strategies for scrutinizing images which affect diagnostic performance of medical practitioners via an eye-tracking study. A total of 56 subjects with 0 to 18 years of experience participated in the study. Every subject was asked to detect DR from 40 images. The findings indicate that practitioners use mainly two types of strategies characterized by either higher dwell duration or longer track length. The main findings of the study are that higher dwell-based strategy led to higher average accuracy (> 85%) in diagnosis, irrespective of the expertise of practitioner; whereas, the average obtained accuracy with a long-track length-based strategy was dependent on the expertise of the practitioner. In the second part of the paper, we use the experimental findings to recommend a scanning strategy for fast and accurate diagnosis of DR that can be potentially used by image readers. This is derived by combining the eye-tracking gaze maps of medical experts in a novel manner based on a set of rules. This strategy requires scrutiny of images in a manner which is consistent with spatial preferences found in human perception in general and in the domain of fundus images in particular. The Levenshtein distance-based assessment of gaze patterns also establish the effectiveness of the derived scanning pattern and is thus recommended for image readers.
关键词： eye-tracking,visual perception,diagnostic strategies,Diabetic retinopathy,medical imaging
更新于2025-09-10 09:29:36