AIMC Topic: Radiography

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Deep learning for categorization of endodontic lesion based on radiographic periapical index scoring system.

Clinical oral investigations Jul 2, 2021
OBJECTIVE: The study aimed to apply convolutional neural network (CNN) to score periapical lesion on an intraoral periapical radiograph (IOPAR) based on the periapical index (PAI) scoring system.
Deep Learning Predictive Value of Tests Radiography
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Semi-supervised classification of radiology images with NoTeacher: A teacher that is not mean.

Medical image analysis Jul 1, 2021
Deep learning models achieve strong performance for radiology image classification, but their practical application is bottlenecked by the need for large labeled training datasets. Semi-supervised learning (SSL) approaches leverage small labeled data...
Humans Radiography Radiology Supervised Machine Learning
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Accuracy of automated identification of lateral cephalometric landmarks using cascade convolutional neural networks on lateral cephalograms from nationwide multi-centres.

Orthodontics & craniofacial research Jun 27, 2021
OBJECTIVE: To investigate the accuracy of automated identification of cephalometric landmarks using the cascade convolutional neural networks (CNN) on lateral cephalograms acquired from nationwide multi-centres.
Anatomic Landmarks Cephalometry Humans Reproducibility of Results Radiography Neural Networks, Computer
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Automatic Detection and Classification of Multiple Catheters in Neonatal Radiographs with Deep Learning.

Journal of digital imaging Jun 25, 2021
We develop and evaluate a deep learning algorithm to classify multiple catheters on neonatal chest and abdominal radiographs. A convolutional neural network (CNN) was trained using a dataset of 777 neonatal chest and abdominal radiographs, with a spl...
Deep Learning Radiography Retrospective Studies Infant, Newborn Humans Catheters Neural Networks, Computer
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Chest radiographs and machine learning - Past, present and future.

Journal of medical imaging and radiation oncology Jun 25, 2021
Despite its simple acquisition technique, the chest X-ray remains the most common first-line imaging tool for chest assessment globally. Recent evidence for image analysis using modern machine learning points to possible improvements in both the effi...
Machine Learning Thorax Humans Image Processing, Computer-Assisted Radiography
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Automating Periodontal bone loss measurement via dental landmark localisation.

International journal of computer assisted radiology and surgery Jun 21, 2021
PURPOSE: Periodontitis is the sixth most prevalent disease worldwide and periodontal bone loss (PBL) detection is crucial for its early recognition and establishment of the correct diagnosis and prognosis. Current radiographic assessment by clinician...
Radiography Observer Variation Alveolar Bone Loss Neural Networks, Computer Periodontitis Humans
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Automated detection of cervical ossification of the posterior longitudinal ligament in plain lateral radiographs of the cervical spine using a convolutional neural network.

Scientific reports Jun 16, 2021
Cervical ossification of the posterior longitudinal ligament (OPLL) is a contributing factor to spinal cord injury or trauma-induced myelopathy in the elderly. To reduce the incidence of these traumas, it is essential to diagnose OPLL at an early sta...
Diagnosis, Differential Radiography Humans Female Spondylosis Cervical Vertebrae Aged Sensitivity and Specificity Neural Networks, Computer Ossification of Posterior Longitudinal Ligament Male
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An Efficient CNN for Hand X-Ray Classification of Rheumatoid Arthritis.

Journal of healthcare engineering Jun 14, 2021
Hand Radiography (RA) is one of the prime tests for checking the progress of rheumatoid joint inflammation in human bone joints. Recognizing the specific phase of RA is a difficult assignment, as human abilities regularly curb the techniques for it. ...
Hand Humans Arthritis, Rheumatoid X-Rays Neural Networks, Computer Radiography
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How does artificial intelligence in radiology improve efficiency and health outcomes?

Pediatric radiology Jun 12, 2021
Since the introduction of artificial intelligence (AI) in radiology, the promise has been that it will improve health care and reduce costs. Has AI been able to fulfill that promise? We describe six clinical objectives that can be supported by AI: a ...
Radiology Outcome Assessment, Health Care Contrast Media Radiography Humans Artificial Intelligence
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Radiology "forensics": determination of age and sex from chest radiographs using deep learning.

Emergency radiology Jun 5, 2021
PURPOSE: To develop and test the performance of deep convolutional neural networks (DCNNs) for automated classification of age and sex on chest radiographs (CXR).
Young Adult Adult Aged Aged, 80 and over Infant Deep Learning Adolescent Male Middle Aged Neural Networks, Computer Female Humans Radiography, Thoracic Child, Preschool Radiography Child Radiology
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