U-net and its variants for medical image segmentation: A review of theory and applications
U-net is an image segmentation technique developed primarily for image segmentation
tasks. These traits provide U-net with a high utility within the medical imaging community …
tasks. These traits provide U-net with a high utility within the medical imaging community …
[Retracted] Discovering Knee Osteoarthritis Imaging Features for Diagnosis and Prognosis: Review of Manual Imaging Grading and Machine Learning Approaches
Knee osteoarthritis (OA) is a deliberating joint disorder characterized by cartilage loss that
can be captured by imaging modalities and translated into imaging features. Observing …
can be captured by imaging modalities and translated into imaging features. Observing …
Modality specific U-Net variants for biomedical image segmentation: a survey
With the advent of advancements in deep learning approaches, such as deep convolution
neural network, residual neural network, adversarial network; U-Net architectures are most …
neural network, residual neural network, adversarial network; U-Net architectures are most …
AI-based automatic detection and classification of diabetic retinopathy using U-Net and deep learning
A Bilal, L Zhu, A Deng, H Lu, N Wu - Symmetry, 2022 - mdpi.com
Artificial intelligence is widely applied to automate Diabetic retinopathy diagnosis. Diabetes-
related retinal vascular disease is one of the world's most common leading causes of …
related retinal vascular disease is one of the world's most common leading causes of …
A novel approach for diabetic retinopathy screening using asymmetric deep learning features
Automatic screening of diabetic retinopathy (DR) is a well-identified area of research in the
domain of computer vision. It is challenging due to structural complexity and a marginal …
domain of computer vision. It is challenging due to structural complexity and a marginal …
A Transfer Learning and U-Net-based automatic detection of diabetic retinopathy from fundus images
Diabetic retinopathy (DR) is an ocular manifestation of diabetes and the leading cause of
visual impairment and blindness across the globe. Early detection and treatment of DR can …
visual impairment and blindness across the globe. Early detection and treatment of DR can …
Brain stroke lesion segmentation using consistent perception generative adversarial network
The state-of-the-art deep learning methods have demonstrated impressive performance in
segmentation tasks. However, the success of these methods depends on a large amount of …
segmentation tasks. However, the success of these methods depends on a large amount of …
VddNet: Vine disease detection network based on multispectral images and depth map
Vine pathologies generate several economic and environmental problems, causing serious
difficulties for the viticultural activity. The early detection of vine disease can significantly …
difficulties for the viticultural activity. The early detection of vine disease can significantly …
Motion-aware needle segmentation in ultrasound images
Segmenting a moving needle in ultrasound images is challenging due to the presence of
artifacts noise and needle occlusion. This task becomes even more demanding in scenarios …
artifacts noise and needle occlusion. This task becomes even more demanding in scenarios …
A deep-learning framework for metacarpal-head cartilage-thickness estimation in ultrasound rheumatological images
Objective Rheumatoid arthritis (RA) is a chronic disease characterized by erosive
symmetrical polyarthritis. Bone and cartilage are the main joint targets of this disease …
symmetrical polyarthritis. Bone and cartilage are the main joint targets of this disease …