Deep learning strategies, particularly convolutional neural networks (CNNs), are especially
suited to finding patterns in images and using those patterns for image classification. The …

The manual segmentation of individual retinal layers within optical coherence tomography
(OCT) images is a time-consuming task and is prone to errors. The investigation into …

The choroid layer is a vascular layer in human retina and its main function is to provide
oxygen and support to the retina. Various studies have shown that the thickness of the …

A major goal of analyzing retinal optical coherence tomography (OCT) images is retinal
layer segmentation. Accurate automated algorithms for segmenting smooth continuous layer …

Abstract Background and objectives: Spectral Domain Optical Coherence Tomography (SD-
OCT) is a volumetric imaging technique that allows measuring patterns between layers such …

Automatic and accurate segmentation of anatomical structures on medical images is crucial
for detecting various potential diseases. However, the segmentation performance of …

Optical coherence tomography (OCT) is an optical high-resolution imaging technique for
ophthalmic diagnosis. In this paper, we take advantages of multi-scale input, multi-scale side …

For the study of various retinal diseases, an accurate quantitative analysis of the retinal layer
is essential for assessing the severity of the disease and diagnosing the progression of the …

The benchmark method for the evaluation of breast cancers involves microscopic testing of a
hematoxylin and eosin (H&E)‐stained tissue biopsy. Resurgery is required in 20% to 30% of …

Introduction Diabetic macular edema (DME) is a major cause of vision impairment in the
patients with diabetes. Optical Coherence Tomography (OCT) is an important ophthalmic …