AIMC Topic: Radiography

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[Object Detection Model Utilizing Deep Learning to Identify Retained Surgical Gauze in the Body on Postoperative Radiography: Phantom Study].

Nihon Hoshasen Gijutsu Gakkai zasshi Jan 1, 2021
PURPOSE: Foreign bodies such as a surgical gauze can be retained in the body after surgery and in some cases cannot be detected by postoperative radiography. The aim of this study was to develop an object detection model capable of postsurgical detec...
Humans Radiography, Abdominal Foreign Bodies Deep Learning Radiography
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[Cephalometric analysis of lateral skull X-ray images using soft computing components in the search for key points].

Stomatologiia Jan 1, 2021
THE AIM OF THE STUDY: Was to investigate the efficiency of decoding teleradiological studies using an algorithm based on the use of convolutional neural networks - a simple convolutional architecture, as well as an extended U-Net architecture.
Humans Skull X-Rays Radiography Neural Networks, Computer Image Processing, Computer-Assisted Cephalometry
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Deep learning assistance for tuberculosis diagnosis with chest radiography in low-resource settings.

Journal of X-ray science and technology Jan 1, 2021
Tuberculosis (TB) is a major health issue with high mortality rates worldwide. Recently, tremendous researches of artificial intelligence (AI) have been conducted targeting at TB to reduce the diagnostic burden. However, most researches are conducted...
Tuberculosis Radiography Radiologists Artificial Intelligence Deep Learning Humans
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[Artificial intelligence in oncological radiology : A (p)review].

Der Radiologe Jan 1, 2021
BACKGROUND: Artificial intelligence (AI) has the potential to fundamentally change medicine within the coming decades. Radiological imaging is one of the primary fields of its clinical application.
Humans Radiography Artificial Intelligence Radiology Algorithms Workflow
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Validation of cervical vertebral maturation stages: Artificial intelligence vs human observer visual analysis.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics Dec 1, 2020
INTRODUCTION: This study aimed to develop an artificial neural network (ANN) model for cervical vertebral maturation (CVM) analysis and validate the model's output with the results of human observers.
Observer Variation Radiography Cervical Vertebrae Humans Artificial Intelligence Reproducibility of Results Neural Networks, Computer
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How much deep learning is enough for automatic identification to be reliable?

The Angle orthodontist Nov 1, 2020
OBJECTIVES: To determine the optimal quantity of learning data needed to develop artificial intelligence (AI) that can automatically identify cephalometric landmarks.
Cephalometry Deep Learning Humans Radiography Artificial Intelligence
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Clinician and computer: a study on patient perceptions of artificial intelligence in skeletal radiography.

BMJ health & care informatics Nov 1, 2020
BACKGROUND: Up to half of all musculoskeletal injuries are investigated with plain radiographs. However, high rates of image interpretation error mean that novel solutions such as artificial intelligence (AI) are being explored.
Surveys and Questionnaires Humans Radiography Computers Artificial Intelligence Tomography, X-Ray Computed Female Patients Male Perception
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Current Clinical Applications of Artificial Intelligence in Radiology and Their Best Supporting Evidence.

Journal of the American College of Radiology : JACR Nov 1, 2020
PURPOSE: Despite tremendous gains from deep learning and the promise of artificial intelligence (AI) in medicine to improve diagnosis and save costs, there exists a large translational gap to implement and use AI products in real-world clinical situa...
Diagnostic Imaging Radiology Artificial Intelligence Algorithms Radiography
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Workflow Applications of Artificial Intelligence in Radiology and an Overview of Available Tools.

Journal of the American College of Radiology : JACR Nov 1, 2020
In the past decade, there has been tremendous interest in applying artificial intelligence (AI) to improve the field of radiology. Currently, numerous AI applications are in development, with potential benefits spanning all steps of the imaging chain...
Radiography Humans Workflow Radiology Artificial Intelligence Radiologists
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Is Deep Learning On Par with Human Observers for Detection of Radiographically Visible and Occult Fractures of the Scaphoid?

Clinical orthopaedics and related research Nov 1, 2020
BACKGROUND: Preliminary experience suggests that deep learning algorithms are nearly as good as humans in detecting common, displaced, and relatively obvious fractures (such as, distal radius or hip fractures). However, it is not known whether this a...
Orthopedic Surgeons Observation Scaphoid Bone Radiography Fractures, Closed Humans Young Adult Adult Middle Aged Deep Learning Male Female Neural Networks, Computer Reproducibility of Results Retrospective Studies
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