Orthopedics

Domain-invariant interpretable fundus image quality assessment.

Objective and quantitative assessment of fundus image quality is essential for the diagnosis of retinal diseases. The major factors in fundus image quality assessment are image artifact, clarity, and field definition. Unfortunately, most of existing quality assessment methods focus on the quality of overall image, without interpretable quality feedback for real-time adjustment. Furthermore, these ...

Estimation of absolute states of human skeletal muscle via standard B-mode ultrasound imaging and deep convolutional neural networks.

The objective is to test automated estimation of active and passive skeletal muscle states using ultrasonic imaging. Current technology (electromyography, dynamometry, shear wave imaging) provides no general, non-invasive method for online estimation of skeletal muscle states. Ultrasound (US) allows non-invasive imaging of muscle, yet current computational approaches have never achieved simultane...

New Insights and Methods in the Approach to Thalassemia Major: The Lesson From the Case of Adrenal Insufficiency.

Thalassemia Major (TM) is a complex pathology that needs a highly skilled approach. Endocrine comorbidities are nowadays the most important complicat...

The Use of Artificial Intelligence in the Evaluation of Knee Pathology.

Artificial intelligence (AI) holds the potential to revolutionize the field of radiology by increasing the efficiency and accuracy of both interpretiv...

Pattern Recognition in Musculoskeletal Imaging Using Artificial Intelligence.

Artificial intelligence (AI) has the potential to affect every step of the radiology workflow, but the AI application that has received the most press...

Artificial intelligence in bone age assessment: accuracy and efficiency of a novel fully automated algorithm compared to the Greulich-Pyle method.

BACKGROUND: Bone age (BA) assessment performed by artificial intelligence (AI) is of growing interest due to improved accuracy, precision and time eff...

Using Deep Learning in Ultrasound Imaging of Bicipital Peritendinous Effusion to Grade Inflammation Severity.

Inflammation of the long head of the biceps tendon is a common cause of shoulder pain. Bicipital peritendinous effusion (BPE) is the most common bicep...

Self-calibrated brain network estimation and joint non-convex multi-task learning for identification of early Alzheimer's disease.

Detection of early stages of Alzheimer's disease (AD) (i.e., mild cognitive impairment (MCI)) is important to maximize the chances to delay or prevent...

Preliminary experience with an image-free handheld robot for total knee arthroplasty: 77 cases compared with a matched control group.

BACKGROUND: Achieving an optimal limb alignment is an important factor affecting the long-term survival of total knee arthroplasty (TKA). This is the ...

A 3D deep supervised densely network for small organs of human temporal bone segmentation in CT images.

Computed Tomography (CT) has become an important way for examining the critical anatomical organs of the human temporal bone in the diagnosis and trea...

Toward automatic quantification of knee osteoarthritis severity using improved Faster R-CNN.

PURPOSE: Knee osteoarthritis (OA) is a common disease that impairs knee function and causes pain. Radiologists usually review knee X-ray images and gr...

Deep learning in fracture detection: a narrative review.

Artificial intelligence (AI) is a general term that implies the use of a computer to model intelligent behavior with minimal human intervention. AI, p...

A multi-scale framework with unsupervised joint training of convolutional neural networks for pulmonary deformable image registration.

To achieve accurate and fast deformable image registration (DIR) for pulmonary CT, we proposed a Multi-scale DIR framework with unsupervised Joint tra...

Semi-supervised learning for automatic segmentation of the knee from MRI with convolutional neural networks.

BACKGROUND AND OBJECTIVE: Segmentation is a crucial step in multiple biomechanics and orthopedics applications. The time-intensiveness and expertise r...

Research on motion planning for an indoor spray arm based on an improved potential field method.

The target spraying effect of spray robots mainly depends on the control performance of the spraying arm during the processes of aiming and tracking. ...

Compact Bone Surgery Robot With a High-Resolution and High-Rigidity Remote Center of Motion Mechanism.

OBJECTIVE: Two important and difficult tasks during a bone drilling procedure are guiding the orientation of the drilling axis toward the target and m...

Predictive validity of radiographic signs of complete discoid lateral meniscus in children using machine learning techniques.

The diagnostic utility of radiographic signs of complete discoid lateral meniscus remains controversial. This study aimed to investigate the diagnosti...

How will digitalisation affect patient treatment in arthroplasty? Part I: Intraoperative aspects.

We cannot deny that technology has become an important part of our daily life, not only in automobiles, houses or cellphones but also in hospitals. In...

Unsupervised machine learning for the discovery of latent disease clusters and patient subgroups using electronic health records.

Machine learning has become ubiquitous and a key technology on mining electronic health records (EHRs) for facilitating clinical research and practice...

Family history information extraction via deep joint learning.

Family history (FH) information, including family members, side of family of family members (i.e., maternal or paternal), living status of family memb...