Explainable AI (XAI) has found numerous applications in computer vision. While image
classification-based explainability techniques have garnered significant attention, their …

Deep learning, particularly convolutional neural networks (CNNs), has revolutionized
endoscopic image processing, significantly enhancing the efficiency and accuracy of …

Extensive research on retinal layer segmentation (RLS) using deep learning (DL) is mostly
approaching a performance plateau, primarily due to reliance on structural information …

The efficient pointer meter reading methods have been proposed based on machine vision
to replace time-consuming manual inspections for the industrial monitoring. However, the …

Variations in the thickness of retinal layers serve as early diagnostic indicators for various
fundus diseases, and precise segmentation of these layers is essential for accurately …

Abstract Changes in retinal thickness and the morphology of fluid provide valuable
diagnostic information for Macular Edema (ME). Optical Coherence Tomography (OCT) is a …

Learning-based general segmentation methods have demonstrated outstanding
performance across many problems in the field of computer vision, showcasing a certain …

Optical coherence tomography (OCT) retinal layer segmentation is a critical procedure of the
modern ophthalmic process, which can be used for diagnosis and treatment of diseases …

High-resolution retinal optical coherence tomography (OCT) images are crucial for the
diagnosis of numerous retinal diseases, but images acquired by narrow bandwidth OCT …

The accurate segmentation of retinal vessels in fundus images is a great challenge in
medical image segmentation tasks due to their highly complex structure from other organs …