[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 …
study introduces the Fundus-DeepNet system, an automated multi-label deep learning …
Retinal vessel segmentation with skeletal prior and contrastive loss
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 …
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 …
advancement and has seen immense applications in multiple domains. Specifically, image …
Self-supervised vessel segmentation via adversarial learning
Vessel segmentation is critically essential for diagnosinga series of diseases, eg, coronary
artery disease and retinal disease. However, annotating vessel segmentation maps of …
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 …
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
Curvilinear object segmentation is critical for many applications. However, manually
annotating curvilinear objects is very time-consuming and error-prone, yielding insufficiently …
annotating curvilinear objects is very time-consuming and error-prone, yielding insufficiently …
Orientation and context entangled network for retinal vessel segmentation
Most existing deep learning based methods for vessel segmentation neglect two important
aspects of retinal vessels: The orientation information of vessels and the contextual …
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 …
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
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 …
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 …
and causes more than 2 million deaths in the world. To achieve this, computer-aided …