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| http://dx.doi.org/10.4103/ijo.IJO_117_22 | DOI Listing |
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Frequency of undiagnosed hypertension among diabetic patients with micro vascular complications.
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Syed Khurram Shehzad, Department of Medicine, Lahore Medical and Dental College, Lahore, Pakistan.
Objectives: To determine the frequency of undiagnosed hypertension among the diabetic patients with micro vascular complications.
Method: This is a descriptive case series conducted at Department of Medicine, Ghurki Trust Teaching Hospital, in this six month stud which enrolled 213 patients between 18-60 years from March 28, 2021 to September 28, 2021, having diabetes with microvascular complications. These patients were not previously diagnosed as hypertensives.
Severity grading of hypertensive retinopathy using hybrid deep learning architecture.
Comput Methods Programs Biomed
January 2025
Regional Institute of Ophthalmology, Indira Gandhi Institute of Medical Sciences, Patna, 800025, Bihar, India.
Background And Objectives: Hypertensive Retinopathy (HR) is a retinal manifestation resulting from persistently elevated blood pressure. Severity grading of HR is essential for patient risk stratification, effective management, progression monitoring, timely intervention, and minimizing the risk of vision impairment. Computer-aided diagnosis and artificial intelligence (AI) systems play vital roles in the diagnosis and grading of HR.
View Article and Find Full Text PDFA Novel Ensemble Meta-Model for Enhanced Retinal Blood Vessel Segmentation Using Deep Learning Architectures.
Biomedicines
January 2025
Perception, Robotics, and Intelligent Machines Lab (PRIME), Department of Computer Science, Université de Moncton, Moncton, NB E1A 3E9, Canada.
Retinal blood vessel segmentation plays an important role in diagnosing retinal diseases such as diabetic retinopathy, glaucoma, and hypertensive retinopathy. Accurate segmentation of blood vessels in retinal images presents a challenging task due to noise, low contrast, and the complex morphology of blood vessel structures. In this study, we propose a novel ensemble learning framework combining four deep learning architectures: U-Net, ResNet50, U-Net with a ResNet50 backbone, and U-Net with a transformer block.
View Article and Find Full Text PDFAssociation of arterial stiffness and eye disease: a systematic review and meta-analysis.
BMJ Open Ophthalmol
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School of Population Health, University of Auckland, Auckland, New Zealand
Background: This systematic review and meta-analysis assesses the association of arterial stiffness with age-related macular degeneration (AMD), glaucoma, retinal vein occlusion (RVO) and retinopathy (diabetic and hypertensive).
Methods: Medline and Embase were systematically searched for observational studies of arterial stiffness and eye disease. Cohort studies were included if they estimated arterial stiffness using any measures based on the arterial waveform, with cross-sectional and case-control studies limited to measures of pulse wave velocity.
DAU-Net: a novel U-Net with dual attention for retinal vessel segmentation.
Biomed Phys Eng Express
January 2025
Faculty of Information Technology, Beijing University of Technology, Beijing, People's Republic of China.
In fundus images, precisely segmenting retinal blood vessels is important for diagnosing eye-related conditions, such as diabetic retinopathy and hypertensive retinopathy or other eye-related disorders. In this work, we propose an enhanced U-shaped network with dual-attention, named DAU-Net, divided into encoder and decoder parts. Wherein, we replace the traditional convolutional layers with ConvNeXt Block and SnakeConv Block to strengthen its recognition ability for different forms of blood vessels while lightweight the model.
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