Generative adversarial networks in medical image segmentation: A review
S Xun, D Li, H Zhu, M Chen, J Wang, J Li… - Computers in biology …, 2022 - Elsevier
Abstract Purpose Since Generative Adversarial Network (GAN) was introduced into the field
of deep learning in 2014, it has received extensive attention from academia and industry …
of deep learning in 2014, it has received extensive attention from academia and industry …
Emergence of deep learning in knee osteoarthritis diagnosis
Osteoarthritis (OA), especially knee OA, is the most common form of arthritis, causing
significant disability in patients worldwide. Manual diagnosis, segmentation, and …
significant disability in patients worldwide. Manual diagnosis, segmentation, and …
A survey on deep learning in medicine: Why, how and when?
New technologies are transforming medicine, and this revolution starts with data. Health
data, clinical images, genome sequences, data on prescribed therapies and results …
data, clinical images, genome sequences, data on prescribed therapies and results …
Systematic review of generative adversarial networks (GANs) for medical image classification and segmentation
In recent years, generative adversarial networks (GANs) have gained tremendous popularity
for various imaging related tasks such as artificial image generation to support AI training …
for various imaging related tasks such as artificial image generation to support AI training …
Generative adversarial networks and its applications in the biomedical image segmentation: a comprehensive survey
Recent advancements with deep generative models have proven significant potential in the
task of image synthesis, detection, segmentation, and classification. Segmenting the medical …
task of image synthesis, detection, segmentation, and classification. Segmenting the medical …
The QIBA profile for MRI-based compositional imaging of knee cartilage
MRI-based cartilage compositional analysis shows biochemical and microstructural
changes at early stages of osteoarthritis before changes become visible with structural MRI …
changes at early stages of osteoarthritis before changes become visible with structural MRI …
Studying osteoarthritis with artificial intelligence applied to magnetic resonance imaging
The 3D nature and soft-tissue contrast of MRI makes it an invaluable tool for osteoarthritis
research, by facilitating the elucidation of disease pathogenesis and progression. The recent …
research, by facilitating the elucidation of disease pathogenesis and progression. The recent …
Generative adversarial networks: a primer for radiologists
Artificial intelligence techniques involving the use of artificial neural networks—that is, deep
learning techniques—are expected to have a major effect on radiology. Some of the most …
learning techniques—are expected to have a major effect on radiology. Some of the most …
[HTML][HTML] Understanding the role and adoption of artificial intelligence techniques in rheumatology research: an in-depth review of the literature
The major and upward trend in the number of published research related to rheumatic and
musculoskeletal diseases, in which artificial intelligence plays a key role, has exhibited the …
musculoskeletal diseases, in which artificial intelligence plays a key role, has exhibited the …
Magnetic resonance imaging assessments for knee segmentation and their use in combination with machine/deep learning as predictors of early osteoarthritis …
J Martel-Pelletier, P Paiement… - Therapeutic Advances …, 2023 - journals.sagepub.com
Knee osteoarthritis (OA) is a prevalent and disabling disease that can develop over
decades. This disease is heterogeneous and involves structural changes in the whole joint …
decades. This disease is heterogeneous and involves structural changes in the whole joint …