Automated retinal image analysis holds prime significance in the accurate diagnosis of
various critical eye diseases that include diabetic retinopathy (DR), age-related macular …

In contrast to conventional optical imaging modalities, hyperspectral imaging (HSI) is able to
capture much more information from a certain scene, both within and beyond the visual …

Background and objective Automatic segmentation of skin lesions in dermoscopy images is
still a challenging task due to the large shape variations and indistinct boundaries of the …

The retinal vascular condition is a reliable biomarker of several ophthalmologic and
cardiovascular diseases, so automatic vessel segmentation may be crucial to diagnose and …

Retinal vessel segmentation is a fundamental step for various ocular imaging applications.
In this paper, we formulate the retinal vessel segmentation problem as a boundary detection …

Automatic segmentation of the retinal vasculature and the optic disc is a crucial task for
accurate geometric analysis and reliable automated diagnosis. In recent years …

An overview of the applications of deep learning for ophthalmic diagnosis using retinal
fundus images is presented. We describe various retinal image datasets that can be used for …

Retinal image analysis holds an imperative position for the identification and classification of
retinal diseases such as Diabetic Retinopathy (DR), Age Related Macular Degeneration …

The segmentation of blood vessels through color fundus images is a difficult and time-
consuming task that requires experienced clinicians. Recently, researchers have shown that …

Vessel segmentation is a key step for various medical applications. This paper introduces
the deep learning architecture to improve the performance of retinal vessel segmentation …