Orthopedics

Emerging trends and research foci of deep learning in spine: bibliometric and visualization study.

As the cognition of spine develops, deep learning (DL) emerges as a powerful tool with tremendous potential for advancing research in this field. To provide a comprehensive overview of DL-spine research, our study utilized bibliometric and visual methods to retrieve relevant articles from the Web of Science database. VOSviewer and CiteSpace were primarily used for literature measurement and knowle...

Active mesh and neural network pipeline for cell aggregate segmentation.

Segmenting cells within cellular aggregates in 3D is a growing challenge in cell biology due to improvements in capacity and accuracy of microscopy techniques. Here, we describe a pipeline to segment images of cell aggregates in 3D. The pipeline combines neural network segmentations with active meshes. We apply our segmentation method to cultured mouse mammary gland organoids imaged over 24 h with...

Artificial intelligence-aided lytic spinal bone metastasis classification on CT scans.

PURPOSE: Spinal bone metastases directly affect quality of life, and patients with lytic-dominant lesions are at high risk for neurological symptoms a...

Deep learning-based detection of patients with bone metastasis from Japanese radiology reports.

PURPOSE: Deep learning (DL) is a state-of-the-art technique for developing artificial intelligence in various domains and it improves the performance ...

Deep Learning-Enabled Morphometric Analysis for Toxicity Screening Using Zebrafish Larvae.

Toxicology studies heavily rely on morphometric analysis to detect abnormalities and diagnose disease processes. The emergence of ever-increasing vari...

Incidental findings on CT scans for robot-assisted total joint arthroplasty.

INTRODUCTION: This study documented the incidence of incidental findings from preoperative computerized-tomography (CT) scans obtained for robotic-arm...

A virtuous cycle between invertebrate and robotics research: perspective on a decade of Living Machines research.

Many invertebrates are ideal model systems on which to base robot design principles due to their success in solving seemingly complex tasks across dom...

Robot-Assisted Kyphoplasty versus Fluoroscopy-Assisted Kyphoplasty: A Meta-Analysis of Postoperative Outcomes.

Osteoporotic vertebral compression fractures are the most common manifestation of osteoporosis. Percutaneous kyphoplasty (PKP) can lead to both pain i...

Precise acetabular positioning, discrepancy in leg length, and hip offset using a new seven-axis robot-assisted total hip arthroplasty system requires no learning curve: a retrospective study.

OBJECTIVE: The purpose of the present study was to determine the learning curve for a novel seven-axis robot-assisted total hip arthroplasty (RA-THA) ...

Convolutional neural network-based automated maxillary alveolar bone segmentation on cone-beam computed tomography images.

OBJECTIVES: To develop and assess the performance of a novel artificial intelligence (AI)-driven convolutional neural network (CNN)-based tool for aut...

Deep learning-based artificial intelligence model for classification of vertebral compression fractures: A multicenter diagnostic study.

OBJECTIVE: To develop and validate an artificial intelligence diagnostic system based on X-ray imaging data for diagnosing vertebral compression fract...

Joint action with human and robotic co-actors: Self-other integration is immune to the perceived humanness of the interacting partner.

When performing a joint action task, we automatically represent the action and/or task constraints of the co-actor with whom we are interacting. Curre...

Automated, calibration-free quantification of cortical bone porosity and geometry in postmenopausal osteoporosis from ultrashort echo time MRI and deep learning.

BACKGROUND: Assessment of cortical bone porosity and geometry by imaging in vivo can provide useful information about bone quality that is independent...

Development and multi-institutional validation of a convolutional neural network to detect vertebral body mis-alignments in 2D x-ray setup images.

BACKGROUND: Misalignment to the incorrect vertebral body remains a rare but serious patient safety risk in image-guided radiotherapy (IGRT).

AMLnet, A deep-learning pipeline for the differential diagnosis of acute myeloid leukemia from bone marrow smears.

Acute myeloid leukemia (AML) is a deadly hematological malignancy. Cellular morphology detection of bone marrow smears based on the French-American-Br...

Automatic deep learning-based assessment of spinopelvic coronal and sagittal alignment.

PURPOSE: The purpose of this study was to evaluate an artificial intelligence (AI) solution for estimating coronal and sagittal spinopelvic alignment ...

Artificial Intelligence for Automated Implant Identification in Knee Arthroplasty: A Multicenter External Validation Study Exceeding 3.5 Million Plain Radiographs.

BACKGROUND: Surgical management of complications following knee arthroplasty demands accurate and timely identification of implant manufacturer and mo...

A Critical Review on Factors Affecting the User Adoption of Wearable and Soft Robotics.

In recent years, the advent of soft robotics has changed the landscape of wearable technologies. Soft robots are highly compliant and malleable, thus ...

Does robot-assisted percutaneous hollow screw placement combined with tarsal sinus incision reduction in the treatment of calcaneal fracture perform better at a minimum two year follow-up compared with traditional surgical reduction and fixation?

PURPOSE: We aimed to evaluate the safety and efficacy of robot-assisted percutaneous hollow screw placement combined with tarsal sinus incisions for t...

Framework for dual-energy-like chest radiography image synthesis from single-energy computed tomography based on cycle-consistent generative adversarial network.

BACKGROUND: Dual-energy (DE) chest radiography (CXR) enables the selective imaging of two relevant materials, namely, soft tissue and bone structures,...