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 …
[HTML][HTML] Unified focal loss: Generalising dice and cross entropy-based losses to handle class imbalanced medical image segmentation
Automatic segmentation methods are an important advancement in medical image analysis.
Machine learning techniques, and deep neural networks in particular, are the state-of-the-art …
Machine learning techniques, and deep neural networks in particular, are the state-of-the-art …
[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 …
SDMT: spatial dependence multi-task transformer network for 3D knee MRI segmentation and landmark localization
Knee segmentation and landmark localization from 3D MRI are two significant tasks for
diagnosis and treatment of knee diseases. With the development of deep learning …
diagnosis and treatment of knee diseases. With the development of deep learning …
Expediting finite element analyses for subject-specific studies of knee osteoarthritis: a literature review
Osteoarthritis (OA) is a degenerative disease that affects the synovial joints, especially the
knee joint, diminishing the ability of patients to perform daily physical activities …
knee joint, diminishing the ability of patients to perform daily physical activities …
Deep learning applications in osteoarthritis imaging
Deep learning (DL) is one of the most exciting new areas in medical imaging. This article will
provide a review of current applications of DL in osteoarthritis (OA) imaging, including …
provide a review of current applications of DL in osteoarthritis (OA) imaging, including …
Realistic CT data augmentation for accurate deep‐learning based segmentation of head and neck tumors in kV images acquired during radiation therapy
Background Using radiation therapy (RT) to treat head and neck (H&N) cancers requires
precise targeting of the tumor to avoid damaging the surrounding healthy organs …
precise targeting of the tumor to avoid damaging the surrounding healthy organs …
[HTML][HTML] Automated knee cartilage segmentation for heterogeneous clinical MRI using generative adversarial networks with transfer learning
Background This study aimed to build a deep learning model to automatically segment
heterogeneous clinical MRI scans by optimizing a pre-trained model built from a …
heterogeneous clinical MRI scans by optimizing a pre-trained model built from a …
[HTML][HTML] Osteoarthritis year in review 2021: imaging
EHG Oei, J Hirvasniemi, TA van Zadelhoff… - Osteoarthritis and …, 2022 - Elsevier
Purpose To provide a narrative review of original articles on imaging of osteoarthritis (OA)
published between January 1, 2020 and March 31, 2021, with a special focus on imaging of …
published between January 1, 2020 and March 31, 2021, with a special focus on imaging of …