Orthopedics

Development and clinical validation of a deep learning-based knee CT image segmentation method for robotic-assisted total knee arthroplasty.

BACKGROUND: This study aimed to develop a novel deep convolutional neural network called Dual-path Double Attention Transformer (DDA-Transformer) designed to achieve precise and fast knee joint CT image segmentation and to validate it in robotic-assisted total knee arthroplasty (TKA).

EUFormer: Learning Driven 3D Spine Deformity Assessment with Orthogonal Optical Images

In clinical settings, the screening, diagnosis, and monitoring of adolescent idiopathic scoliosis (AIS) typically involve physical or radiographic examinations. However, physical examinations are subjective, while radiographic examinations expose patients to harmful radiation. Consequently, we propose a pipeline that can accurately determine scoliosis severity. This pipeline utilizes posteroante...

Braille-to-Speech Generator: Audio Generation Based on Joint Fine-Tuning of CLIP and Fastspeech2

An increasing number of Chinese people are troubled by different degrees of visual impairment, which has made the modal conversion between a single ...

LiteGPT: Large Vision-Language Model for Joint Chest X-ray Localization and Classification Task

Vision-language models have been extensively explored across a wide range of tasks, achieving satisfactory performance; however, their application i...

The Growing Role of Artificial Intelligence and Technology in Hip and Knee Arthroplasty.

Artificial intelligence and technology have continued to evolve over recent decades, and their utility in hip and knee arthroplasty is growing with in...

Interobserver Agreement and Performance of Concurrent AI Assistance for Radiographic Evaluation of Knee Osteoarthritis.

Background Due to conflicting findings in the literature, there are concerns about a lack of objectivity in grading knee osteoarthritis (KOA) on radio...

A Three-Stage Semi-Supervised Learning Approach to Spine Image Segmentation.

Spine segmentation in computed tomography (CT) images is critical for automatic analysis, especially when focusing on varied spinal anatomy. Despite h...

EUFormer: Learning Driven 3D Spine Deformity Assessment with Orthogonal Optical Images.

In clinical settings, the screening, diagnosis, and monitoring of adolescent idiopathic scoliosis (AIS) typically involve physical or radiographic exa...

Vertebrae Segmentation with Generative Adversarial Networks for Automatic Cobb Angle Measurement.

Scoliosis is a lateral deformity of the spine, usually diagnosed in patients with a Cobb angle (CA) greater than 10°. Accurate measurements of the CA ...

An Explainable and Conformal AI Model to Detect Temporomandibular Joint Involvement in Children Suffering from Juvenile Idiopathic Arthritis.

Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease during childhood and adolescence. The temporomandibular joints (TMJ) are amon...

Ultrasound for Automated Classification of Full-Thickness Rotator Cuff Tendon Tears using Deep Learning.

Rotator cuff tendon tears, the most common shoulder injuries, are typically diagnosed mainly through MRI, but can also be seen on ultrasound (US), a m...

Single Bone Modeler: deep learning bone segmentation for cone-beam CT.

The accurate segmentation and modeling of bones play a crucial role in diagnosis and surgical planning in orthopedics. Traditional methods face challe...

Hip Hiking Gait Improvement with Electrohydraulic Robotic Knee: Preliminary Results.

Individuals with Transfemoral Amputation (TFA) usually exhibit hip hiking walking with passive prostheses due to insufficient knee flexion. Powered kn...

Development of Mobile Application Based on AI for Predicting the Suitable Height of High Heels.

As high heels become increasingly popular in everyday attire, their impact on foot and lower limb health has garnered widespread attention. Wearing hi...

Preliminary Experimental Validation of a Cable-Driven Joint System for Custom Orthoses.

Robot-assisted gait training has the potential to enhance gait therapy for children with mobility impairments. Robotic orthoses are designed to improv...

A Multimodal Transfer Learning Approach for Histopathology and SR-microCT Low-Data Regimes Image Segmentation.

Osteocyte-lacunar bone structures are a discerning marker for bone pathophysiology, given their geometric alterations observed during aging and diseas...

Classification of Abnormal Gaits with Machine Learning Algorithms using Sensor-Inherited Insoles.

The digital health industry's interest in gait analysis has driven research into sensor-enabled insoles for practical, everyday gait monitoring. Tradi...

Prediction of Low Bone Mass for Japanese Female Athletes Using Machine Learning.

Attainment of optimal bone mineral density (BMD) in female athletes is a very important aspect of ensuring their well-being throughout their lives, an...

SimICL: A Simple Visual In-context Learning Framework for Ultrasound Segmentation.

Conventional deep learning models deal with images one-by-one, requiring costly and time-consuming expert labeling in the field of medical imaging, an...

FRA-DiagSys: A Transformer Winding Fault Diagnosis System for Identifying Fault Types and degrees Using Frequency Response Analysis

The electric power transformer is a critical component in electrical distribution networks, and the diagnosis of faults in transformers is an import...