Latest AI and machine learning research in orthopedics for healthcare professionals.
Reducing CO$_2$ emissions is crucial to mitigating climate change. Carbon Capture and Storage (CCS) is one of the few technologies capable of achieving net-negative CO$_2$ emissions. However, predicting fluid flow patterns in CCS remains challenging due to uncertainties in CO$_2$ plume dynamics and reservoir properties. Building on existing seismic imaging methods like the Joint Recovery Method ...
Human motion generation is a significant pursuit in generative computer vision with widespread applications in film-making, video games, AR/VR, and human-robot interaction. Current methods mainly utilize either diffusion-based generative models or autoregressive models for text-to-motion generation. However, they face two significant challenges: (1) The generation process is time-consuming, posi...
Understanding internal joint loading is critical for diagnosing gait-related diseases such as knee osteoarthritis; however, current methods of measu...
A crucial aspect in phase-field modeling, based on the variational formulation of brittle fracture, is the accurate representation of how the fractu...
There has been substantial progress in humanoid robots, with new skills continuously being taught, ranging from navigation to manipulation. While th...
Bone metastasis analysis is a significant challenge in pathology and plays a critical role in determining patient quality of life and treatment stra...
This study forms the basis of a digital twin system of the knee joint, using advanced quantitative MRI (qMRI) and machine learning to advance precis...
3D object detection and occupancy prediction are critical tasks in autonomous driving, attracting significant attention. Despite the potential of re...
Advances in computer vision, particularly in optical image-based 3D reconstruction and feature matching, enable applications like marker-less surgic...
Human pose estimation has given rise to a broad spectrum of novel and compelling applications, including action recognition, sports analysis, as wel...
Background: Multiparametric breast MRI data might improve tumor diagnostics, characterization, and treatment planning. Accurate alignment and deline...
Foundation models hold transformative potential for medical imaging, but their clinical utility requires rigorous evaluation to address their streng...
Diffusion models are state-of-the-art for image generation. Trained on large datasets, they capture expressive image priors that have been used for ...
Glaucoma is a leading cause of irreversible blindness worldwide, emphasizing the critical need for early detection and intervention. In this paper, ...
In this paper, a novel learning-based Wyner-Ziv coding framework is considered under a distributed image transmission scenario, where the correlated...
Deep learning-based joint source-channel coding (JSCC) is emerging as a promising technology for effective image transmission. However, most existin...
2D portrait animation has experienced significant advancements in recent years. Much research has utilized the prior knowledge embedded in large gen...
Canine cardiomegaly, marked by an enlarged heart, poses serious health risks if undetected, requiring accurate diagnostic methods. Current detection...
Medical image segmentation is challenging due to the diversity of medical images and the lack of labeled data, which motivates recent developments i...
The conversion from 2D X-ray to 3D shape holds significant potential for improving diagnostic efficiency and safety. However, existing reconstructio...