Segmentation of lesions from fundus images is an essential prerequisite for accurate
severity assessment of diabetic retinopathy. Due to variation in morphologies, number and …

Background Large vessel occlusion (LVO) stroke is one of the most time-sensitive
diagnoses in medicine and requires emergent endovascular therapy to reduce morbidity …

With recent advanced technologies, various automated diagnosis tools were developed to
prevent retinal diseases. The automatic segmentation of blood vessels can help detect …

Segmentation of diabetic retinopathy is a significant requirement for correct severity
estimation level. Due to dissimilarity in shapes, size, and quantity of retinal lesions, the …

Atherosclerosis is a common cause of cardiac attack and its early detection prevents further
complications. In this paper, a research concept is proposed focusing on a novel method of …

Research for identifying osteoporosis using dental radiographic images is increasing
rapidly. Subjects data from various regions and countries have been used by many …

Biomedical image analysis based on metaheuristic algorithms is one of the most important
research areas encountered in recent years. Due to the low contrast differences between the …

Changes in retinal blood vessels are a characteristic sign of many retinal diseases.
Therefore, the automatic segmentation of vessels is an essential element for the diagnosis of …

The fundamental components of automated retinal blood vessel segmentation for eye
disease screening systems are segmentation algorithms, retinal blood vessel datasets …

This article analyzes the sensitivity of deep learning methods for ocular fundus
segmentation. We use an empirical methodology based on non‐adversarial perturbed …