Latest AI and machine learning research in orthopedics for healthcare professionals.
Generalization in medical segmentation models is challenging due to limited annotated datasets and imaging variability. To address this, we propose Retinal Layout-Aware Diffusion (RLAD), a novel diffusion-based framework for generating controllable layout-aware images. RLAD conditions image generation on multiple key layout components extracted from real images, ensuring high structural fidelity...
Medical Foundation Models (MFMs), trained on large-scale datasets, have demonstrated superior performance across various tasks. However, these models still struggle with domain gaps in practical applications. Specifically, even after fine-tuning on source-domain data, task-adapted foundation models often perform poorly in the target domain. To address this challenge, we propose a few-shot unsupe...
Accurate gait event detection is crucial for gait analysis, rehabilitation, and assistive technology, particularly in exoskeleton control, where pre...
OBJECTIVES: Although deep learning has demonstrated substantial potential in automatic quantification of joint damage in RA, evidence for detecting lo...
Purpose To construct and evaluate the performance of a machine learning model for bone segmentation using whole-body CT images. Materials and Methods ...
BACKGROUND: Artificial intelligence has been shown to achieve successful outcomes in various orthopedic qualification examinations worldwide. This stu...
Background Recent studies have investigated how deep learning (DL) algorithms applied to CT using two-dimensional (2D) segmentation (sagittal or axial...
The complex mechanical environment of peripheral arteries makes stents with poor torsional performance more prone to fracture, and stent fracture is c...
Despite significant progress in diffusion-based image generation, subject-driven generation and instruction-based editing remain challenging. Existi...
We present a system for decoding hand movements using surface EMG signals. The interface provides real-time (25 Hz) reconstruction of finger joint a...
In today's digital landscape, Deep Recommender Systems (DRS) play a crucial role in navigating and customizing online content for individual prefere...
Glaucomatous optic neuropathy (GON) is a prevalent ocular disease that can lead to irreversible vision loss if not detected early and treated. The t...
Fundus image quality is crucial for diagnosing eye diseases, but real-world conditions often result in blurred or unreadable images, increasing diag...
Deploying natural language generation systems in clinical settings remains challenging despite advances in Large Language Models (LLMs), which conti...
Existing communication systems aim to reconstruct the information at the receiver side, and are known as reconstruction-oriented communications. Thi...
Hip exoskeletons are increasing in popularity due to their effectiveness across various scenarios and their ability to adapt to different users. How...
Optical coherence tomography angiography (OCTA) is a non-invasive imaging technique widely used to study vascular structures and micro-circulation d...
2D image coding for machines (ICM) has achieved great success in coding efficiency, while less effort has been devoted to stereo image fields. To pr...
This paper introduces a novel Hybrid Visual Servoing (HVS) approach for controlling tendon-driven continuum robots (TDCRs). The HVS system combines ...
Despite recent advances in learning-based controllers for legged robots, deployments in human-centric environments remain limited by safety concerns...