Orthopedics

Can AI distinguish a bone radiograph from photos of flowers or cars? Evaluation of bone age deep learning model on inappropriate data inputs.

OBJECTIVE: To evaluate the behavior of a publicly available deep convolutional neural network (DCNN) bone age algorithm when presented with inappropriate data inputs in both radiological and non-radiological domains.

Artificial intelligence in orthopedic implant model classification: a systematic review.

Although artificial intelligence models have demonstrated high accuracy in identifying specific orthopedic implant models from imaging, which is an important and time-consuming task, the scope of prior works and performance of prior models have not been evaluated. We performed a systematic review to summarize the scope, methodology, and performance of artificial intelligence algorithms in classify...

Estimating Reference Bony Shape Models for Orthognathic Surgical Planning Using 3D Point-Cloud Deep Learning.

Orthognathic surgical outcomes rely heavily on the quality of surgical planning. Automatic estimation of a reference facial bone shape significantly r...

Deep learning in knee imaging: a systematic review utilizing a Checklist for Artificial Intelligence in Medical Imaging (CLAIM).

PURPOSE: Our purposes were (1) to explore the methodologic quality of the studies on the deep learning in knee imaging with CLAIM criterion and (2) to...

Automatic segmentation of the temporomandibular joint disc on magnetic resonance images using a deep learning technique.

OBJECTIVES: The aims of the present study were to construct a deep learning model for automatic segmentation of the temporomandibular joint (TMJ) disc...

Estimating Human Pose Efficiently by Parallel Pyramid Networks.

Good performance and high efficiency are both critical for estimating human pose in practice. Recent state-of-the-art methods have greatly boosted the...

CT-based thermometry with virtual monoenergetic images by dual-energy of fat, muscle and bone using FBP, iterative and deep learning-based reconstruction.

OBJECTIVES: The aim of this study was to evaluate the sensitivity of CT-based thermometry for clinical applications regarding a three-component tissue...

Deep Learning-Based Denoised MRI Images for Correlation Analysis between Lumbar Facet Joint and Lumbar Disc Herniation in Spine Surgery.

This work aimed to explore the relationship between spine surgery lumbar facet joint (LFJ) and lumbar disc herniation (LDH) via compressed sensing alg...

A Novel Pressure-Controlled Revolute Joint with Variable Stiffness.

The compliance and deformability of soft robotics allow human-machine interactions in a safe manner without the need of sophisticated control systems ...

Robot-assisted Exploration of Somatic Nerves in the Pelvis and Transection of the Sacrospinous Ligament for Alcock Canal Syndrome.

STUDY OBJECTIVE: Some articles have reported the surgical management of Alcock canal syndrome (ACS) using the transperineal [1], transgluteal [2], or ...

Bone collision detection method for robot assisted fracture reduction based on force curve slope.

BACKGROUND AND OBJECTIVE: The application of robot technology in fracture reduction ensures the minimal invasiveness and accurate operation process. M...

2D-3D reconstruction of distal forearm bone from actual X-ray images of the wrist using convolutional neural networks.

The purpose of the study was to develop a deep learning network for estimating and constructing highly accurate 3D bone models directly from actual X-...

LPAQR-Net: Efficient Vertebra Segmentation From Biplanar Whole-Spine Radiographs.

Vertebra segmentation from biplanar whole-spine radiographs is highly demanded in the quantitative assessment of scoliosis and the resultant sagittal ...

Interpretable and Lightweight 3-D Deep Learning Model for Automated ACL Diagnosis.

We propose an interpretable and lightweight 3D deep neural network model that diagnoses anterior cruciate ligament (ACL) tears from a knee MRI exam. P...

Deep Learning in the Detection of Rare Fractures - Development of a "Deep Learning Convolutional Network" Model for Detecting Acetabular Fractures.

BACKGROUND: Fracture detection by artificial intelligence and especially Deep Convolutional Neural Networks (DCNN) is a topic of growing interest in c...

Deep radiomics-based survival prediction in patients with chronic obstructive pulmonary disease.

Heterogeneous clinical manifestations and progression of chronic obstructive pulmonary disease (COPD) affect patient health risk assessment, stratific...

Joint fully convolutional and graph convolutional networks for weakly-supervised segmentation of pathology images.

Tissue/region segmentation of pathology images is essential for quantitative analysis in digital pathology. Previous studies usually require full supe...

Deep neural network approach for estimating the three-dimensional human center of mass using joint angles.

Human body center of mass location plays an essential role in physical therapy, especially in investigating a subject's capability to maintain balance...

Machine learning reveals mesenchymal breast carcinoma cell adaptation in response to matrix stiffness.

Epithelial-mesenchymal transition (EMT) and its reverse process, mesenchymal-epithelial transition (MET), are believed to play key roles in facilitati...

Equal bony resection of distal and posterior femur will lead to flexion/extension gap inequality in robot-assisted cruciate-retaining TKA.

PURPOSE: Joint imbalance has become one of the main reasons for early revision after total knee arthroplasty (TKA) and it is directly related to the s...