AIMC Topic: Radiography

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Detection of pulpal calcifications on bite-wing radiographs using deep learning.

Clinical oral investigations Dec 23, 2022
OBJECTIVES: Pulpal calcifications are discrete hard calcified masses of varying sizes in the dental pulp cavity. This study is aimed at measuring the performance of the YOLOv4 deep learning algorithm to automatically determine whether there is calcif...
Dental Pulp Calcification Humans Radiography Deep Learning Dental Pulp Cavity
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Machine Learning Model for Chest Radiographs: Using Local Data to Enhance Performance.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Dec 21, 2022
PURPOSE: To develop and assess the performance of a machine learning model which screens chest radiographs for 14 labels, and to determine whether fine-tuning the model on local data improves its performance. Generalizability at different institution...
Deep Learning Neural Networks, Computer Retrospective Studies Machine Learning Humans Radiography
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Deep Learning for Breast MRI Style Transfer with Limited Training Data.

Journal of digital imaging Dec 21, 2022
In this work we introduce a novel medical image style transfer method, StyleMapper, that can transfer medical scans to an unseen style with access to limited training data. This is made possible by training our model on unlimited possibilities of sim...
Humans Magnetic Resonance Imaging Radiography Image Processing, Computer-Assisted Deep Learning
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Detecting Distal Radius Fractures Using a Segmentation-Based Deep Learning Model.

Journal of digital imaging Dec 21, 2022
Deep learning algorithms can be used to classify medical images. In distal radius fracture treatment, fracture detection and radiographic assessment of fracture displacement are critical steps. The aim of this study was to use pixel-level annotations...
Wrist Fractures Radiography Retrospective Studies Deep Learning Algorithms Humans
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Can artificial intelligence pass the Fellowship of the Royal College of Radiologists examination? Multi-reader diagnostic accuracy study.

BMJ (Clinical research ed.) Dec 21, 2022
OBJECTIVE: To determine whether an artificial intelligence candidate could pass the rapid (radiographic) reporting component of the Fellowship of the Royal College of Radiologists (FRCR) examination.
Radiography Retrospective Studies Fellowships and Scholarships Radiologists Artificial Intelligence Prospective Studies Humans
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Knowledge, perceptions, and expectations of Artificial intelligence in radiography practice: A global radiography workforce survey.

Journal of medical imaging and radiation sciences Dec 18, 2022
BACKGROUND: Artificial Intelligence (AI) technologies have already started impacting clinical practice across various settings worldwide, including the radiography profession. This study is aimed at exploring a world-wide view on AI technologies in r...
Radiography Workforce Surveys and Questionnaires Motivation Artificial Intelligence Humans
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Focus on machine learning models in medical imaging.

Physics in medicine and biology Dec 16, 2022
Radiography Diagnostic Imaging Machine Learning
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Transparency in Artificial Intelligence Research: a Systematic Review of Availability Items Related to Open Science in Radiology and Nuclear Medicine.

Academic radiology Dec 14, 2022
RATIONALE AND OBJECTIVES: Reproducibility of artificial intelligence (AI) research has become a growing concern. One of the fundamental reasons is the lack of transparency in data, code, and model. In this work, we aimed to systematically review the ...
Artificial Intelligence Reproducibility of Results Humans Radiography Radionuclide Imaging Nuclear Medicine
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Automatic assessment of knee osteoarthritis severity in portable devices based on deep learning.

Journal of orthopaedic surgery and research Dec 14, 2022
BACKGROUND: For knee osteoarthritis, the commonly used radiology severity criteria Kellgren-Lawrence lead to variability among surgeons. Most existing diagnosis models require preprocessed radiographs and specific equipment.
Osteoarthritis, Knee Deep Learning Humans Knee Joint Radiography
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Diagnosis of nasal bone fractures on plain radiographs via convolutional neural networks.

Scientific reports Dec 13, 2022
This study aimed to assess the performance of deep learning (DL) algorithms in the diagnosis of nasal bone fractures on radiographs and compare it with that of experienced radiologists. In this retrospective study, 6713 patients whose nasal radiograp...
Humans Neural Networks, Computer Fractures, Bone Radiography Deep Learning Retrospective Studies
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