Orthopedics

Glowing Sucker Octopus (Stauroteuthis syrtensis)-Inspired Soft Robotic Gripper for Underwater Self-Adaptive Grasping and Sensing.

A soft gripper inspired by the glowing sucker octopus (Stauroteuthis syrtensis)' highly evolved grasping capability enabled by the umbrella-shaped dorsal and ventral membrane between each arm is presented here, comprising of a 3D-printed linkage mechanism used to actuate a modular mold silicone-casting soft suction disc to deform. The soft gripper grasp can lift objects using the suction generated...

Assessment of deep convolutional neural network models for mandibular fracture detection in panoramic radiographs.

The aim of this study was to develop automated models for the identification and detection of mandibular fractures in panoramic radiographs using convolutional neural network (CNN) algorithms. A total of 1710 panoramic radiograph images from the years 2016 to 2020, including 855 images containing mandibular fractures, were obtained retrospectively from the regional trauma centre. CNN-based classif...

Deep learning-based framework for segmentation of multiclass rib fractures in CT utilizing a multi-angle projection network.

PURPOSE: Clinical rib fracture diagnosis via computed tomography (CT) screening has attracted much attention in recent years. However, automated and a...

Accuracy and safety of robot-assisted cortical bone trajectory screw placement: a comparison of robot-assisted technique with fluoroscopy-assisted approach.

OBJECTIVE: To compare the safety and accuracy of cortical bone trajectory screw placement between the robot-assisted and fluoroscopy-assisted approach...

Fully Automated Abdominal CT Biomarkers for Type 2 Diabetes Using Deep Learning.

Background CT biomarkers both inside and outside the pancreas can potentially be used to diagnose type 2 diabetes mellitus. Previous studies on this t...

A Deep Learning Method for Foot Progression Angle Detection in Plantar Pressure Images.

Foot progression angle (FPA) analysis is one of the core methods to detect gait pathologies as basic information to prevent foot injury from excessive...

Automatic prosthetic-parameter estimation from anteroposterior pelvic radiographs after total hip arthroplasty using deep learning-based keypoint detection.

BACKGROUND: X-ray is a necessary tool for post-total hip arthroplasty (THA) check-ups; however, parameter measurements are time-consuming. We proposed...

Can uncertainty estimation predict segmentation performance in ultrasound bone imaging?

PURPOSE: Segmenting bone surfaces in ultrasound (US) is a fundamental step in US-based computer-assisted orthopaedic surgeries. Neural network-based s...

Design and evaluation of an intelligent reduction robot system for the minimally invasive reduction in pelvic fractures.

INTRODUCTION: Pelvic fracture is a severe high-energy injury with the highest disability and mortality of all fractures. Traditional open surgery is a...

Two-Stage CNN Model for Joint Demosaicing and Denoising of Burst Bayer Images.

In the classical image processing pipeline, demosaicing and denoising are separated steps that may interfere with each other. Joint demosaicing and de...

Automatic recognition of whole-spine sagittal alignment and curvature analysis through a deep learning technique.

PURPOSE: Artificial intelligence based on deep learning (DL) approaches enables the automatic recognition of anatomic landmarks and subsequent estimat...

Detection of Differences in Longitudinal Cartilage Thickness Loss Using a Deep-Learning Automated Segmentation Algorithm: Data From the Foundation for the National Institutes of Health Biomarkers Study of the Osteoarthritis Initiative.

OBJECTIVE: To study the longitudinal performance of fully automated cartilage segmentation in knees with radiographic osteoarthritis (OA), we evaluate...

Prior information-based high-resolution tomography image reconstruction from a single digitally reconstructed radiograph.

Tomography images are essential for clinical diagnosis and trauma surgery, allowing doctors to understand the internal information of patients in more...

A two-stage deep learning architecture for radiographic staging of periodontal bone loss.

BACKGROUND: Radiographic periodontal bone loss is one of the most important basis for periodontitis staging, with problems such as limited accuracy, i...

DeBoNet: A deep bone suppression model ensemble to improve disease detection in chest radiographs.

Automatic detection of some pulmonary abnormalities using chest X-rays may be impacted adversely due to obscuring by bony structures like the ribs and...

Navigated and Robot-Assisted Technology in Total Knee Arthroplasty: Do Outcome Differences Achieve Minimal Clinically Important Difference?

BACKGROUND: In total knee arthroplasty (TKA), computer-assisted navigation (N-TKA) and robotic-assisted methods (RA-TKA) are intended to increase prec...

Deep learning reconstruction for 1.5 T cervical spine MRI: effect on interobserver agreement in the evaluation of degenerative changes.

OBJECTIVES: To investigate whether deep learning reconstruction (DLR) provides improved cervical spine MR images using a 1.5 T unit in the evaluation ...

Artificial Intelligence in Fracture Detection: A Systematic Review and Meta-Analysis.

Background Patients with fractures are a common emergency presentation and may be misdiagnosed at radiologic imaging. An increasing number of studies ...

Deep learning for the dynamic prediction of multivariate longitudinal and survival data.

The joint model for longitudinal and survival data improves time-to-event predictions by including longitudinal outcome variables in addition to basel...

Development of deep learning algorithms to discriminate giant cell tumors of bone from adjacent normal tissues by confocal Raman spectroscopy.

Raman spectroscopy is a non-destructive analysis technique that provides detailed information about the chemical structure of tumors. Raman spectra of...