[HTML][HTML] Fundus-deepnet: Multi-label deep learning classification system for enhanced detection of multiple ocular diseases through data fusion of fundus images

S Al-Fahdawi, AS Al-Waisy, DQ Zeebaree, R Qahwaji… - Information …, 2024 - Elsevier
Detecting multiple ocular diseases in fundus images is crucial in ophthalmic diagnosis. This
study introduces the Fundus-DeepNet system, an automated multi-label deep learning …

Retinal vessel segmentation with skeletal prior and contrastive loss

Y Tan, KF Yang, SX Zhao, YJ Li - IEEE Transactions on Medical …, 2022 - ieeexplore.ieee.org
The morphology of retinal vessels is closely associated with many kinds of ophthalmic
diseases. Although huge progress in retinal vessel segmentation has been achieved with …

Features to text: a comprehensive survey of deep learning on semantic segmentation and image captioning

A Oluwasammi, MU Aftab, Z Qin, ST Ngo, TV Doan… - …, 2021 - Wiley Online Library
With the emergence of deep learning, computer vision has witnessed extensive
advancement and has seen immense applications in multiple domains. Specifically, image …

Self-supervised vessel segmentation via adversarial learning

Y Ma, Y Hua, H Deng, T Song… - Proceedings of the …, 2021 - openaccess.thecvf.com
Vessel segmentation is critically essential for diagnosinga series of diseases, eg, coronary
artery disease and retinal disease. However, annotating vessel segmentation maps of …

Computational intelligence in eye disease diagnosis: a comparative study

SVM Kumar, R Gunasundari - Medical & Biological Engineering & …, 2023 - Springer
In recent years, eye disorders are an important health issue among older people. Generally,
individuals with eye diseases are unaware of the gradual growth of symptoms. Therefore …

FreeCOS: self-supervised learning from fractals and unlabeled images for curvilinear object segmentation

T Shi, X Ding, L Zhang, X Yang - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
Curvilinear object segmentation is critical for many applications. However, manually
annotating curvilinear objects is very time-consuming and error-prone, yielding insufficiently …

Orientation and context entangled network for retinal vessel segmentation

X Wei, K Yang, D Bzdok, Y Li - Expert Systems with Applications, 2023 - Elsevier
Most existing deep learning based methods for vessel segmentation neglect two important
aspects of retinal vessels: The orientation information of vessels and the contextual …

Width attention based convolutional neural network for retinal vessel segmentation

DE Alvarado-Carrillo, OS Dalmau-Cedeño - Expert Systems with …, 2022 - Elsevier
The analysis of the vascular tree is a fundamental part of the clinical assessment of retinal
images. The diversity of blood vessel calibers and curvatures, as well as the ocular vascular …

A two-stage GAN for high-resolution retinal image generation and segmentation

P Andreini, G Ciano, S Bonechi, C Graziani, V Lachi… - Electronics, 2021 - mdpi.com
In this paper, we use Generative Adversarial Networks (GANs) to synthesize high-quality
retinal images along with the corresponding semantic label-maps, instead of real images …

Computer-aided detection of COVID-19 from CT images based on Gaussian mixture model and kernel support vector machines classifier

A Saygılı - Arabian Journal for Science and Engineering, 2022 - Springer
COVID-19 is a virus that has been declared an epidemic by the world health organization
and causes more than 2 million deaths in the world. To achieve this, computer-aided …