Latest AI and machine learning research in orthopedics for healthcare professionals.
Multimodal data is a precious asset enabling a variety of downstream tasks in machine learning. However, real-world data collected across different modalities is often not paired, which is a significant challenge to learn a joint distribution. A prominent approach to address the modality coupling problem is Minimum Entropy Coupling (MEC), which seeks to minimize the joint Entropy, while satisfyi...
Contrastive Language-Image Pre-Training (CLIP) is a popular method for learning multimodal latent spaces with well-organized semantics. Despite its wide range of applications, CLIP's latent space is known to fail at handling complex visual-textual interactions. Recent works attempt to address its shortcomings with data-centric or algorithmic approaches. But what if the problem is more fundamenta...
This paper presents a novel method for estimating the orientation and the position of acetabular hip implants in total hip arthroplasty using full a...
This paper introduces PoseLess, a novel framework for robot hand control that eliminates the need for explicit pose estimation by directly mapping 2...
The increasing pace of population aging calls for better care and support systems. Falling is a frequent and critical problem for elderly people cau...
Freehand 3D ultrasound enables volumetric imaging by tracking a conventional ultrasound probe during freehand scanning, offering enriched spatial in...
While diffusion distillation has enabled one-step generation through methods like Variational Score Distillation, adapting distilled models to emerg...
This paper focuses on multimodal alignment within the realm of Artificial Intelligence, particularly in text and image modalities. The semantic gap ...
Cervical spondylosis, a complex and prevalent condition, demands precise and efficient diagnostic techniques for accurate assessment. While MRI offe...
Osteoporotic vertebral compression fractures (VCFs) are prevalent in the elderly population, typically assessed on computed tomography (CT) scans by...
Graphical modeling is a widely used tool for analyzing conditional dependencies between variables and traditional methods may struggle to capture sh...
Self-modeling enables robots to build task-agnostic models of their morphology and kinematics based on data that can be automatically collected, wit...
The joint bidiagonalization (JBD) process of a regular matrix pair $\{A,L\}$ is mathematically equivalent to two simultaneous Lanczos bidiagonalizat...
Calculating percentage bone loss is a critical test for periodontal disease staging but is sometimes imprecise and time consuming when manually calc...
Existing state-of-the-art feature matchers capture long-range dependencies with Transformers but are hindered by high spatial complexity, leading to...
Automated defect detection in industrial manufacturing is essential for maintaining product quality and minimizing production errors. In air disc br...
This study investigates a pulsating fluid jet as a novel precise, minimally invasive and cold technique for bone cement removal. We utilize the puls...
Objective: we propose a procedure for calibrating 4 parameters governing the mechanical boundary conditions (BCs) of a thoracic aorta (TA) model der...
Rapid bone scintigraphy is an essential tool for diagnosing skeletal diseases and tumor metastasis in pediatric patients, as it reduces scan time an...
The increasing prevalence of lumbar spinal canal stenosis has resulted in a surge of MRI (Magnetic Resonance Imaging), leading to labor-intensive in...