Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039310
This paper proposes an automatic method to identify important positions and their color features in retinal fundus images for gender classification using deep learning. The proposed method consists of MALCC (Model Analysis by Local Color Characterist...
Journal of the Optical Society of America. A, Optics, image science, and vision
39889019
As we all know, suppressing noise while maintaining detailed structure has been a challenging problem in the field of image enhancement, especially for color retinal images. In this paper, a dual-channel lightweight GAN named dilated shuffle generati...
Feature extraction in ML plays a crucial role in transforming raw data into a more meaningful and interpretable representation. In this study, we thoroughly examined a range of feature extraction techniques and assessed their impact on the binary cla...
PURPOSE: This study aimed to initially test whether machine learning approaches could categorically predict two simple biological features, mouse age and mouse species, using the retinal segmentation metrics.
Wide-field optical coherence tomography (OCT) imaging can enable monitoring of peripheral changes in the retina, beyond the conventional fields of view used in current clinical OCT imaging systems. However, wide-field scans can present significant ch...
Therapeutic protocols involving subretinal injection, which hold the promise of saving or restoring sight, are challenging for surgeons because they are at the limits of human motor and perceptual abilities. Excessive or insufficient indentation of t...
OBJECTIVE: Hyperreflective foci (HRF) are small, punctate lesions ranging from 20 to 50 m and exhibiting high reflective intensity in optical coherence tomography (OCT) images of patients with diabetic retinopathy (DR). The purpose of the model prop...
PURPOSE: The purpose of this study was to provide the development of a method to classify optical coherence tomography (OCT)-assessed retinal data in the context of automatic diagnosis of early-stage multiple sclerosis (MS) with decision explanation.
BACKGROUND: Chronic kidney disease (CKD) is a prevalent condition with significant global health implications. Early detection and management are critical to prevent disease progression and complications. Deep learning (DL) models using retinal image...
Captured retinal images vary greatly in quality. Low-quality images increase the risk of misdiagnosis. This motivates to design effective retinal image quality assessment (RIQA) methods. Current deep learning-based methods usually classify the image ...