Orthopedics

Super-resolution reconstruction of knee magnetic resonance imaging based on deep learning.

BACKGROUND AND OBJECTIVE: With the rapid development of medical imaging and intelligent diagnosis, artificial intelligence methods have become a research hotspot of radiography processing technology in recent years. The low definition of knee magnetic resonance image texture seriously affects the diagnosis of knee osteoarthritis. This paper presents a super-resolution reconstruction method to addr...

Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs.

PURPOSE: To develop and validate a deep learning (DL) algorithm that predicts referable glaucomatous optic neuropathy (GON) and optic nerve head (ONH) features from color fundus images, to determine the relative importance of these features in referral decisions by glaucoma specialists (GSs) and the algorithm, and to compare the performance of the algorithm with eye care providers.

Using machine learning to understand neuromorphological change and image-based biomarker identification in Cavalier King Charles Spaniels with Chiari-like malformation-associated pain and syringomyelia.

BACKGROUND: Chiari-like malformation (CM) is a complex malformation of the skull and cranial cervical vertebrae that potentially results in pain and s...

The sense of agency in human-human vs human-robot joint action.

Kinesthesis pertains to the perception of moving body parts, while the sense of agency refers to the experience of controlling one's action-effects. B...

Decentralized control with cross-coupled sensory feedback between body and limbs in sprawling locomotion.

Quadrupeds achieve rapid and highly adaptive locomotion owing to the coordination between their legs and other body parts such as their trunk, head, a...

Sequential Saliency Guided Deep Neural Network for Joint Mitosis Identification and Localization in Time-Lapse Phase Contrast Microscopy Images.

The analysis of cell mitotic behavior plays important role in many biomedical research and medical diagnostic applications. To improve the accuracy of...

Integrating joint feature selection into subspace learning: A formulation of 2DPCA for outliers robust feature selection.

Since the principal component analysis and its variants are sensitive to outliers that affect their performance and applicability in real world, sever...

Robotic Exoskeleton for Wrist and Fingers Joint in Post-Stroke Neuro-Rehabilitation for Low-Resource Settings.

Robots have the potential to help provide exercise therapy in a repeatable and reproducible manner for stroke survivors. To facilitate rehabilitation ...

Artificial neural network to estimate micro-architectural properties of cortical bone using ultrasonic attenuation: A 2-D numerical study.

The goal of this study is to estimate micro-architectural parameters of cortical porosity such as pore diameter (φ), pore density (ρ) and porosity (ν)...

A Repeatable Motion Scheme for Kinematic Control of Redundant Manipulators.

To achieve closed trajectory motion planning of redundant manipulators, each joint angle has to be returned to its initial position. Most of the repea...

EMG-based lumbosacral joint compression force prediction using a support vector machine.

Electromyography-assisted optimization (EMGAO) approach is widely used to predict lumbar joint loads under various dynamic and static conditions. Howe...

Identification of Vertebral Fractures by Convolutional Neural Networks to Predict Nonvertebral and Hip Fractures: A Registry-based Cohort Study of Dual X-ray Absorptiometry.

Background Detection of vertebral fractures (VFs) aids in management of osteoporosis and targeting of fracture prevention therapies. Purpose To determ...

Automated vertebrae localization and identification by decision forests and image-based refinement on real-world CT data.

PURPOSE: Development of a fully automatic algorithm for the automatic localization and identification of vertebral bodies in computed tomography (CT).

Coupled artificial neural networks to estimate 3D whole-body posture, lumbosacral moments, and spinal loads during load-handling activities.

Biomechanical modeling approaches require body posture to evaluate the risk of spine injury during manual material handling. The procedure to measure ...

Machine learning predicts putative hematopoietic stem cells within large single-cell transcriptomics data sets.

Hematopoietic stem cells (HSCs) are an essential source and reservoir for normal hematopoiesis, and their function is compromised in many blood disord...

Comprehensive analysis of efficient swimming using articulated legs fringed with flexible appendages inspired by a water beetle.

Drag-based swimming is usually accompanied with the shape change of rowing appendages to generate asymmetric force during the power stroke and recover...

A probabilistic method to estimate gait kinetics in the absence of ground reaction force measurements.

Human joint torques during gait are usually computed using inverse dynamics. This method requires a skeletal model, kinematics and measured ground rea...

An Integrated Sensor-Model Approach for Haptic Feedback of Flexible Endoscopic Robots.

Haptic feedback for flexible endoscopic surgical robots is challenging due to space constraints for sensors and shape-dependent force hysteresis of te...

Development of an automatic muscle atrophy measuring algorithm to calculate the ratio of supraspinatus in supraspinous fossa using deep learning.

BACKGROUND AND OBJECTIVE: Rotator cuff muscle tear is one of the most frequent reason of operations in orthopedic surgery. There are several clinical ...

Predicting Hospital Readmission: A Joint Ensemble-Learning Model.

Hospital readmission is among the most critical issues in the healthcare system due to its high prevalence and cost. The improvement effort necessitat...