Review of artificial intelligence techniques in imaging data acquisition, segmentation, and diagnosis for COVID-19
The pandemic of coronavirus disease 2019 (COVID-19) is spreading all over the world.
Medical imaging such as X-ray and computed tomography (CT) plays an essential role in …
Medical imaging such as X-ray and computed tomography (CT) plays an essential role in …
[HTML][HTML] Surgical data science–from concepts toward clinical translation
Recent developments in data science in general and machine learning in particular have
transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a …
transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a …
[HTML][HTML] The application of unsupervised clustering methods to Alzheimer's disease
Clustering is a powerful machine learning tool for detecting structures in datasets. In the
medical field, clustering has been proven to be a powerful tool for discovering patterns and …
medical field, clustering has been proven to be a powerful tool for discovering patterns and …
Artificial intelligence and internet of things (AI-IoT) technologies in response to COVID-19 pandemic: A systematic review
The origin of the COVID-19 pandemic has given overture to redirection, as well as
innovation to many digital technologies. Even after the progression of vaccination efforts …
innovation to many digital technologies. Even after the progression of vaccination efforts …
Metrabs: metric-scale truncation-robust heatmaps for absolute 3d human pose estimation
Heatmap representations have formed the basis of human pose estimation systems for
many years, and their extension to 3D has been a fruitful line of recent research. This …
many years, and their extension to 3D has been a fruitful line of recent research. This …
Cai4cai: the rise of contextual artificial intelligence in computer-assisted interventions
Data-driven computational approaches have evolved to enable extraction of information
from medical images with reliability, accuracy, and speed, which is already transforming …
from medical images with reliability, accuracy, and speed, which is already transforming …
Computer vision in the surgical operating room
Background: Multiple types of surgical cameras are used in modern surgical practice and
provide a rich visual signal that is used by surgeons to visualize the clinical site and make …
provide a rich visual signal that is used by surgeons to visualize the clinical site and make …
Deep learning for unsupervised domain adaptation in medical imaging: Recent advancements and future perspectives
Deep learning has demonstrated remarkable performance across various tasks in medical
imaging. However, these approaches primarily focus on supervised learning, assuming that …
imaging. However, these approaches primarily focus on supervised learning, assuming that …
A generalizable approach for multi-view 3d human pose regression
A Kadkhodamohammadi, N Padoy - Machine Vision and Applications, 2021 - Springer
Despite the significant improvement in the performance of monocular pose estimation
approaches and their ability to generalize to unseen environments, multi-view approaches …
approaches and their ability to generalize to unseen environments, multi-view approaches …
Anatomy-guided domain adaptation for 3D in-bed human pose estimation
A Bigalke, L Hansen, J Diesel, C Hennigs… - Medical Image …, 2023 - Elsevier
Abstract 3D human pose estimation is a key component of clinical monitoring systems. The
clinical applicability of deep pose estimation models, however, is limited by their poor …
clinical applicability of deep pose estimation models, however, is limited by their poor …