Review of artificial intelligence techniques in imaging data acquisition, segmentation, and diagnosis for COVID-19

F Shi, J Wang, J Shi, Z Wu, Q Wang… - IEEE reviews in …, 2020 - ieeexplore.ieee.org
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 …

Artificial intelligence (AI) for medical imaging to combat coronavirus disease (COVID-19): A detailed review with direction for future research

TA Soomro, L Zheng, AJ Afifi, A Ali, M Yin… - Artificial Intelligence …, 2022 - Springer
Since early 2020, the whole world has been facing the deadly and highly contagious
disease named coronavirus disease (COVID-19) and the World Health Organization …

Jrdb-pose: A large-scale dataset for multi-person pose estimation and tracking

E Vendrow, DT Le, J Cai… - Proceedings of the …, 2023 - openaccess.thecvf.com
Autonomous robotic systems operating in human environments must understand their
surroundings to make accurate and safe decisions. In crowded human scenes with close-up …

Bodies at rest: 3d human pose and shape estimation from a pressure image using synthetic data

HM Clever, Z Erickson, A Kapusta… - Proceedings of the …, 2020 - openaccess.thecvf.com
People spend a substantial part of their lives at rest in bed. 3D human pose and shape
estimation for this activity would have numerous beneficial applications, yet line-of-sight …

Multimodal image registration with deep context reinforcement learning

K Ma, J Wang, V Singh, B Tamersoy, YJ Chang… - … Image Computing and …, 2017 - Springer
Automatic and robust registration between real-time patient imaging and pre-operative data
(eg CT and MRI) is crucial for computer-aided interventions and AR-based navigation …

Human posture recognition using a hybrid of fuzzy logic and machine learning approaches

W Ren, O Ma, H Ji, X Liu - IEEE Access, 2020 - ieeexplore.ieee.org
An autonomous assistive robot needs to recognize the body-limb posture of the person
being assisted while he/she is lying in a bed to provide care services such as hel** …

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 …

Stmt: A spatial-temporal mesh transformer for mocap-based action recognition

X Zhu, PY Huang, J Liang… - Proceedings of the …, 2023 - openaccess.thecvf.com
We study the problem of human action recognition using motion capture (MoCap)
sequences. Unlike existing techniques that take multiple manual steps to derive …

Learning and tracking the 3D body shape of freely moving infants from RGB-D sequences

N Hesse, S Pujades, MJ Black, M Arens… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Statistical models of the human body surface are generally learned from thousands of high-
quality 3D scans in predefined poses to cover the wide variety of human body shapes and …

Neuralvdb: High-resolution sparse volume representation using hierarchical neural networks

D Kim, M Lee, K Museth - ACM Transactions on Graphics, 2024 - dl.acm.org
We introduce NeuralVDB, which improves on an existing industry standard for efficient
storage of sparse volumetric data, denoted VDB [Museth], by leveraging recent …