AIMC Topic: Radiography

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Realistic CT data augmentation for accurate deep-learning based segmentation of head and neck tumors in kV images acquired during radiation therapy.

Medical physics Apr 17, 2023
BACKGROUND: Using radiation therapy (RT) to treat head and neck (H&N) cancers requires precise targeting of the tumor to avoid damaging the surrounding healthy organs. Immobilisation masks and planning target volume margins are used to attempt to mit...
Retrospective Studies Tomography, X-Ray Computed Humans Head and Neck Neoplasms Radiography Deep Learning Image Processing, Computer-Assisted
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Current and potential applications of artificial intelligence in medical imaging practice: A narrative review.

Journal of medical imaging and radiation sciences Apr 14, 2023
BACKGROUND AND PURPOSE: Artificial intelligence (AI) is present in many areas of our lives. Much of the digital data generated in health care can be used for building automated systems to bring improvements to existing workflows and create a more per...
Delivery of Health Care Humans Radiography Artificial Intelligence
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Usefulness of copper filters in digital chest radiography based on the relationship between effective detective quantum efficiency and deep learning-based segmentation accuracy of the tumor area.

Radiological physics and technology Apr 12, 2023
This study aimed to determine the optimal radiographic conditions for detecting lesions on digital chest radiographs using an indirect conversion flat-panel detector with a copper (Cu) filter. First, we calculated the effective detective quantum effi...
Humans Artificial Intelligence Neoplasms Deep Learning Radiography Radiographic Image Enhancement Copper
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Evaluating diagnostic content of AI-generated chest radiography: A multi-center visual Turing test.

PloS one Apr 12, 2023
BACKGROUND: Accurate interpretation of chest radiographs requires years of medical training, and many countries face a shortage of medical professionals to meet such requirements. Recent advancements in artificial intelligence (AI) have aided diagnos...
Neural Networks, Computer Artificial Intelligence Humans Radiography Certification Hospitals, University
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CORR Insights®: Can a Deep Learning Algorithm Improve Detection of Occult Scaphoid Fractures in Plain Radiographs? A Clinical Validation Study.

Clinical orthopaedics and related research Apr 11, 2023
Scaphoid Bone Fractures, Closed Deep Learning Magnetic Resonance Imaging Fractures, Bone Humans Radiography
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Deep-learning-based denoising of X-ray differential phase and dark-field images.

European journal of radiology Apr 11, 2023
PURPOSE: Statistical photon noise has always been a common problem in X-ray multi-contrast imaging and significantly influenced the quality of retrieved differential phase and dark-field images. We intend to develop a deep learning-based denoising al...
X-Rays Deep Learning Humans Radiography Image Processing, Computer-Assisted Algorithms Signal-To-Noise Ratio Tomography, X-Ray Computed
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Deep learning-based prediction of osseointegration for dental implant using plain radiography.

BMC oral health Apr 8, 2023
BACKGROUND: In this study, we investigated whether deep learning-based prediction of osseointegration of dental implants using plain radiography is possible.
Dental Implantation, Endosseous Deep Learning Radiography Dental Implants Osseointegration Humans
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An Endodontic Forecasting Model Based on the Analysis of Preoperative Dental Radiographs: A Pilot Study on an Endodontic Predictive Deep Neural Network.

Journal of endodontics Apr 4, 2023
INTRODUCTION: This study aimed to evaluate the use of deep convolutional neural network (DCNN) algorithms to detect clinical features and predict the three-year outcome of endodontic treatment on preoperative periapical radiographs.
Root Canal Therapy Pilot Projects Radiography Neural Networks, Computer Artificial Intelligence
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[Update: Small bowel diseases in computed tomography and magnetic resonance imaging].

Radiologie (Heidelberg, Germany) Apr 4, 2023
CLINICAL/METHODICAL ISSUE: Radiological procedures play a crucial role in the diagnosis of small bowel disease. Due to a broad and quite nonspecific spectrum of symptoms, clinical evaluation is often difficult, and endoscopic procedures require signi...
Humans Radiography Artificial Intelligence Intestinal Diseases Tomography, X-Ray Computed Ultrasonography Magnetic Resonance Imaging
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Investigating the robustness of a deep learning-based method for quantitative phase retrieval from propagation-based x-ray phase contrast measurements under laboratory conditions.

Physics in medicine and biology Apr 3, 2023
Quantitative phase retrieval (QPR) in propagation-based x-ray phase contrast imaging of heterogeneous and structurally complicated objects is challenging under laboratory conditions due to partial spatial coherence and polychromaticity. A deep learni...
X-Rays Deep Learning Microscopy, Phase-Contrast Radiography
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