Recent trends and advances in fundus image analysis: A review
Automated retinal image analysis holds prime significance in the accurate diagnosis of
various critical eye diseases that include diabetic retinopathy (DR), age-related macular …
various critical eye diseases that include diabetic retinopathy (DR), age-related macular …
A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification
The eye affords a unique opportunity to inspect a rich part of the human microvasculature
non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are …
non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are …
An approach for de-noising and contrast enhancement of retinal fundus image using CLAHE
Now-a-days medical fundus images are widely used in clinical diagnosis for the detection of
retinal disorders. Fundus images are generally degraded by noise and suffer from low …
retinal disorders. Fundus images are generally degraded by noise and suffer from low …
Retinal vessel segmentation via a Multi-resolution Contextual Network and adversarial learning
Timely and affordable computer-aided diagnosis of retinal diseases is pivotal in precluding
blindness. Accurate retinal vessel segmentation plays an important role in disease …
blindness. Accurate retinal vessel segmentation plays an important role in disease …
Width-wise vessel bifurcation for improved retinal vessel segmentation
Vessel local characteristics such as noise, illumination, and direction vary significantly in a
fundus image, making it difficult to segment the vessel tree structure as a whole. To facilitate …
fundus image, making it difficult to segment the vessel tree structure as a whole. To facilitate …
Contrast enhancement of fundus images by employing modified PSO for improving the performance of deep learning models
Computer-Aided diagnosis (CAD) is a widely used technique to detect and diagnose
diseases like tumors, cancers, edemas, etc. Several critical retinal diseases like diabetic …
diseases like tumors, cancers, edemas, etc. Several critical retinal diseases like diabetic …
Residual connection-based encoder decoder network (RCED-Net) for retinal vessel segmentation
Devising automated procedures for accurate vessel segmentation (retinal) is crucial for
timely prognosis of vision-threatening eye diseases. In this paper, a novel supervised deep …
timely prognosis of vision-threatening eye diseases. In this paper, a novel supervised deep …
An efficient and light weight deep learning model for accurate retinal vessels segmentation
Detecting eye diseases early can make a difference when trying to treat them. Existing
diagnostic systems are not only prone to inaccurate judgments, but are also difficult and …
diagnostic systems are not only prone to inaccurate judgments, but are also difficult and …
Prompt deep light-weight vessel segmentation network (PLVS-Net)
Achieving accurate retinal vessel segmentation is critical in the progression and diagnosis of
vision-threatening diseases such as diabetic retinopathy and age-related macular …
vision-threatening diseases such as diabetic retinopathy and age-related macular …
Towards automated eye diagnosis: an improved retinal vessel segmentation framework using ensemble block matching 3D filter
Automated detection of vision threatening eye disease based on high resolution retinal
fundus images requires accurate segmentation of the blood vessels. In this regard, detection …
fundus images requires accurate segmentation of the blood vessels. In this regard, detection …