Automated system for the detection of hypertensive retinopathy

Khitran, Sarmad Abbas; Akram, M. Usman; Usman, Anam; Yasin, Ubaidullah

doi:10.1109/ipta.2014.7001984

Cited by 26 publications

(19 citation statements)

References 13 publications

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“…The proposed model is included in the early screening category, or early detection, when referring to Dahlan's study [17] then the main performance parameters are sensitivity. Referring to the parameter of sensitivity, the proposed model is relatively good compared to a number of existing studies, except with studies conducted by Khitran et.al [7]. The difference in performance with the research of Khitran et.al [7], is possible due to the difference of dataset so that the characteristics of each tested data are different.…”

Section: Results and Analysismentioning

confidence: 73%

“…Referring to the parameter of sensitivity, the proposed model is relatively good compared to a number of existing studies, except with studies conducted by Khitran et.al [7]. The difference in performance with the research of Khitran et.al [7], is possible due to the difference of dataset so that the characteristics of each tested data are different. These differences result in the resulting performance difference.…”

Section: Results and Analysismentioning

confidence: 73%

“…Manikis et.al [5], also proposes a framework for diagnosis of hypertensive retinopathy disease with hessian-based segmentation of blood vessels, then calculate the value of the AVR as a sign of the disease. A number of similar studies, ie, performed a diagnosis of hypertensive retinopathy using AVR parameters such as those performed by Ortiz et.al [6], Khitran et.al [7], Triwijoyo et.al [8], Faheem et.al [9] and Muramatsu et.al [10].…”

Section: Introductionmentioning

confidence: 99%

“…The performance parameters are analyzed is accuracy, PPV, NPV, specificity, sensitivity, and AUC. The performance parameters are calculated based on the formula shown in equation (7)(8)(9)(10)(11)(12). Interpretation of the performance parameters especially AUC has two approaches, namely statistically and clinically.…”

mentioning

confidence: 99%

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Assessment of Early Hypertensive Retinopathy using Fractal Analysis of Retinal Fundus Image

2018

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Section: Results and Analysismentioning

confidence: 73%

Section: Results and Analysismentioning

confidence: 73%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Assessment of Early Hypertensive Retinopathy using Fractal Analysis of Retinal Fundus Image

2018

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“…The limitation of their work was that the AVR calculation has been done only on region (0.5-1) optic disc diameter (DD) which may give inappropriate results according to them. Khitran et al [7] work was based on classification of vessels as arteries and veins using new feature vector. They tested their method on 58 fundus images of VICAVR and 40 images of DRIVE database.…”

Section: Related Workmentioning

confidence: 99%

Measurement of Arterio-Venous Ratio for Detection of Hypertensive Retinopathy through Digital Color Fundus Images

Rani

Mittal

2015

JBEMi

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Hypertensive retinopathy is a retinal vascular damage caused by high blood pressure which results in loss of vision. In the present work, effort has been devoted to enhance and segment the retinal vasculature which is required to calculate its anatomical characteristics such as width, length for the quantitative measurement of arterio-venous ratio (AVR). Enhancement of the retinal fundus images is done using tophat transform and segmentation of the vessels using iterative thresholding. The performance of the proposed method is tested on 50 digital fundus images of publicly available MESSIDOR dataset. The hypertensive retinopathy can be measured quantitatively by detecting the decrement in the ratio of width of retinal artery-vein to that of the normal images. The arterio-venous ratio obtained by applying the proposed methodology was found to be 0.62-0.735 in normal cases and 0.203-0.495 in case of patients suffering from hypertensive retinopathy on MESSIDOR dataset which was not performed earlier. This measurement of arterio-venous ratio will be further helpful to identify the stages of hypertensive retinopathy.

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Diabetic retinopathy detection and classification using hybrid feature set

Amin

Sharif

Rehman

et al. 2018

Microscopy Res & Technique

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Complicated stages of diabetes are the major cause of Diabetic Retinopathy (DR) and no symptoms appear at the initial stage of DR. At the early stage diagnosis of DR, screening and treatment may reduce vision harm. In this work, an automated technique is applied for detection and classification of DR. A local contrast enhancement method is used on grayscale images to enhance the region of interest. An adaptive threshold method with mathematical morphology is used for the accurate lesions region segmentation. After that, the geometrical and statistical features are fused for better classification. The proposed method is validated on DIARETDB1, E‐ophtha, Messidor, and local data sets with different metrics such as area under the curve (AUC) and accuracy (ACC).

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Automated system for the detection of hypertensive retinopathy

Cited by 26 publications

References 13 publications

Assessment of Early Hypertensive Retinopathy using Fractal Analysis of Retinal Fundus Image

Assessment of Early Hypertensive Retinopathy using Fractal Analysis of Retinal Fundus Image

Measurement of Arterio-Venous Ratio for Detection of Hypertensive Retinopathy through Digital Color Fundus Images

Diabetic retinopathy detection and classification using hybrid feature set

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