Latest AI and machine learning research in orthopedics for healthcare professionals.
Accurate prediction of stress and strain fields in hierarchical composite microstructures is critical for physics-informed material design, yet conventional finite element method (FEM) simulations are computationally prohibitive at scale, requiring minutes to days per evaluation. In this work, we propose a hybrid UNet-Transformer architecture that predicts complex mechanical field distributions di...
Vision-language models map images and text into a joint embedding space. However, these embeddings often entangle multiple semantic features, which limits their interpretability and controllability. While sparse autoencoders have emerged as a useful tool for decomposing these embeddings into monosemantic features, their application to joint embedding spaces has largely relied on an implicit, untes...
Recent advances in diffusion models have shown impressive performance in controllable image generation and dense prediction tasks. However, existing a...
Historical encrypted manuscripts present a challenging problem at the intersection of cryptology, linguistics, paleography, and computer vision. Curre...
Sparse Autoencoders (SAEs) have shown promise for analyzing language models, but applying them to vision-language models (VLMs) often yields represent...
Field-scale retrieval of surface soil moisture (SM), leaf area index (LAI), and plant height (PH) is essential for precision agriculture, yet it remai...
Purpose: To investigate how artificial intelligence (AI) systems detect referrable diabetic retinopathy (DR) from retinal photographs by analysing hea...
Background Anthropometric measures do not adequately capture heterogeneity in body fat distribution and corresponding cardiometabolic risk, whereas ma...
Inference-time alignment of pretrained text-to-image models is typically performed along a single control axis, such as classifier-free guidance, atte...
Universal segmentation models exhibit significant potential for diverse tasks involving different imaging modalities and segmentation objectives. Task...
Humans localize places by integrating perceptual cues from vision with semantic reasoning from language, forming a scene understanding that is both in...
Background/Purpose: Diagnosing wrist ligament injuries is challenging; early detection and treatment are important to prevent osteoarthritis progressi...
Cinematic compositing aims to integrate green-screen characters into novel environments while maintaining physical and photometric realism. Previous m...
Pelvic segmentation is one of the most important and fundamental research problems in precise and intelligent diagnosis and treatment, as well as surg...
Models for estimating animal density from camera traps require four parameters informing detection: movement speed, daily activity level, staying time...
The full potential of artificial intelligence in tibial plateau fracture characterisation remains unrealised, constrained by a fundamental dependency ...
The Zygomaticomaxillary Suture is a key circummaxillary structure that connects the zygomatic bone and the maxilla, which serves as a primary site of ...
This work proposes an integrated pipeline for automatic glaucoma detection method from easily available colour fundas images based on an adaptive algo...
Vision Language Model (VLM) has great potential to enhance the quality of pseudo labels in semi-supervised spine segmentation by leveraging textual cl...
As a cornerstone of the central dogma, RNA has both witnessed and actively shaped three billion years of evolution. Over this vast timescale, a remark...