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Retinal Vessels

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A high resolution representation network with multi-path scale for retinal vessel segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Automatic retinal vessel segmentation (RVS) in fundus images is expected to be a vital step in the early image diagnosis of ophthalmologic diseases. However, it is a challenging task to detect the retinal vessel accurately ...

A Global and Local Enhanced Residual U-Net for Accurate Retinal Vessel Segmentation.

IEEE/ACM transactions on computational biology and bioinformatics
Retinal vessel segmentation is a critical procedure towards the accurate visualization, diagnosis, early treatment, and surgery planning of ocular diseases. Recent deep learning-based approaches have achieved impressive performance in retinal vessel ...

Diabetic Retinopathy Fundus Image Classification and Lesions Localization System Using Deep Learning.

Sensors (Basel, Switzerland)
Diabetic retinopathy (DR) is a disease resulting from diabetes complications, causing non-reversible damage to retina blood vessels. DR is a leading cause of blindness if not detected early. The currently available DR treatments are limited to stoppi...

"Keep it simple, scholar": an experimental analysis of few-parameter segmentation networks for retinal vessels in fundus imaging.

International journal of computer assisted radiology and surgery
PURPOSE: With the recent development of deep learning technologies, various neural networks have been proposed for fundus retinal vessel segmentation. Among them, the U-Net is regarded as one of the most successful architectures. In this work, we sta...

A new deep learning method for blood vessel segmentation in retinal images based on convolutional kernels and modified U-Net model.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automatic monitoring of retinal blood vessels proves very useful for the clinical assessment of ocular vascular anomalies or retinopathies. This paper presents an efficient and accurate deep learning-based method for vessel ...

Artificial intelligence in OCT angiography.

Progress in retinal and eye research
Optical coherence tomographic angiography (OCTA) is a non-invasive imaging modality that provides three-dimensional, information-rich vascular images. With numerous studies demonstrating unique capabilities in biomarker quantification, diagnosis, and...

Lightweight pyramid network with spatial attention mechanism for accurate retinal vessel segmentation.

International journal of computer assisted radiology and surgery
PURPOSE: The morphological characteristics of retinal vessels are vital for the early diagnosis of pathological diseases such as diabetes and hypertension. However, the low contrast and complex morphology pose a challenge to automatic retinal vessel ...

Fast and efficient retinal blood vessel segmentation method based on deep learning network.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The segmentation of the retinal vascular tree presents a major step for detecting ocular pathologies. The clinical context expects higher segmentation performance with a reduced processing time. For higher accurate segmentation, several automated met...

Deep Learning-Based Diabetic Retinopathy Severity Grading System Employing Quadrant Ensemble Model.

Journal of digital imaging
The diabetic retinopathy accounts in the deterioration of retinal blood vessels leading to a serious compilation affecting the eyes. The automated DR diagnosis frameworks are critically important for the early identification and detection of these ey...

Robust Content-Adaptive Global Registration for Multimodal Retinal Images Using Weakly Supervised Deep-Learning Framework.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Multimodal retinal imaging plays an important role in ophthalmology. We propose a content-adaptive multimodal retinal image registration method in this paper that focuses on the globally coarse alignment and includes three weakly supervised neural ne...