Orthopedics

Joint optic disc and optic cup segmentation based on boundary prior and adversarial learning.

PURPOSE: The most direct means of glaucoma screening is to use cup-to-disc ratio via colour fundus photography, the first step of which is the precise segmentation of the optic cup (OC) and optic disc (OD). In recent years, convolution neural networks (CNN) have shown outstanding performance in medical segmentation tasks. However, most CNN-based methods ignore the effect of boundary ambiguity on p...

Comparison of Different Technologies for Soft Robotics Grippers.

Soft grippers have experienced a growing interest due to their considerable flexibility that allows them to grasp a variety of objects, in contrast to hard grippers, which are designed for a specific item. One of their most remarkable characteristics is the ability to manipulate soft objects without damaging them. This, together with their wide range of applications and the use of novels materials...

Deep learning methods allow fully automated segmentation of metacarpal bones to quantify volumetric bone mineral density.

Arthritis patients develop hand bone loss, which leads to destruction and functional impairment of the affected joints. High resolution peripheral qua...

Evaluation of an open-source machine-learning tool to quantify bone marrow plasma cells.

AIMS: The objective of this study was to develop and validate an open-source digital pathology tool, QuPath, to automatically quantify CD138-positive ...

Detection of Postural Control in Young and Elderly Adults Using Deep and Machine Learning Methods with Joint-Node Plots.

Postural control decreases with aging. Thus, an efficient and accurate method of detecting postural control is needed. We enrolled 35 elderly adults (...

NeuroCrypt: Machine Learning Over Encrypted Distributed Neuroimaging Data.

The field of neuroimaging can greatly benefit from building machine learning models to detect and predict diseases, and discover novel biomarkers, but...

Artificial intelligence improves the accuracy of residents in the diagnosis of hip fractures: a multicenter study.

BACKGROUND: Less experienced clinicians sometimes make misdiagnosis of hip fractures. We developed computer-aided diagnosis (CAD) system for hip fract...

Development and Validation of a Deep Learning Model Using Convolutional Neural Networks to Identify Scaphoid Fractures in Radiographs.

IMPORTANCE: Scaphoid fractures are the most common carpal fracture, but as many as 20% are not visible (ie, occult) in the initial injury radiograph; ...

Better precision of a new robotically assisted system for total knee arthroplasty compared to conventional techniques: A sawbone model study.

BACKGROUND: The purpose of this study was to compare the accuracy of this new HURWA robotic-assisted total knee arthroplasty (TKA) technique to the ac...

Machine Learning and Intelligent Diagnostics in Dental and Orofacial Pain Management: A Systematic Review.

PURPOSE: The study explored the clinical influence, effectiveness, limitations, and human comparison outcomes of machine learning in diagnosing (1) de...

A deep learning system for automated, multi-modality 2D segmentation of vertebral bodies and intervertebral discs.

PURPOSE: Fractures in vertebral bodies are among the most common complications of osteoporosis and other bone diseases. However, studies that aim to p...

Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment.

Convolutional Neural Networks (CNNs) are statistical models suited for learning complex visual patterns. In the context of Species Distribution Models...

Availability and reporting quality of external validations of machine-learning prediction models with orthopedic surgical outcomes: a systematic review.

Background and purpose - External validation of machine learning (ML) prediction models is an essential step before clinical application. We assessed ...

A method for the automatic detection of myopia in Optos fundus images based on deep learning.

Myopia detection is significant for preventing irreversible visual impairment and diagnosing myopic retinopathy. To improve the detection efficiency a...

Deep learning to segment pelvic bones: large-scale CT datasets and baseline models.

PURPOSE: Pelvic bone segmentation in CT has always been an essential step in clinical diagnosis and surgery planning of pelvic bone diseases. Existing...

Estimation of the Continuous Walking Angle of Knee and Ankle (Talocrural Joint, Subtalar Joint) of a Lower-Limb Exoskeleton Robot Using a Neural Network.

A lower-limb exoskeleton robot identifies the wearer's walking intention and assists the walking movement through mechanical force; thus, it is import...

Automatic tip detection of surgical instruments in biportal endoscopic spine surgery.

BACKGROUND: Recent advances in robotics and deep learning can be used in endoscopic surgeries and can provide numerous advantages by freeing one of th...

Model construction and application for automated measurement of CE angle on pelvis orthograph based on MASK-R-CNN algorithm.

Developmental dysplasia of the hip (DDH) is a common orthopedic disease. A simple and cost-effective scientific tool for assisting the early diagnosis...

Adaptive SNN for Anthropomorphic Finger Control.

Anthropomorphic hands that mimic the smoothness of human hand motions should be controlled by artificial units of high biological plausibility. Adapta...

Accelerated multicontrast reconstruction for synthetic MRI using joint parallel imaging and variable splitting networks.

PURPOSE: Synthetic magnetic resonance imaging (MRI) requires the acquisition of multicontrast images to estimate quantitative parameter maps, such as ...