AIMC Topic: Radiography

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Enhanced detection of threat materials by dark-field x-ray imaging combined with deep neural networks.

Nature communications Sep 9, 2022
X-ray imaging has been boosted by the introduction of phase-based methods. Detail visibility is enhanced in phase contrast images, and dark-field images are sensitive to inhomogeneities on a length scale below the system's spatial resolution. Here we...
Radiography X-Rays Microscopy, Phase-Contrast Neural Networks, Computer Machine Learning
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SplitAVG: A Heterogeneity-Aware Federated Deep Learning Method for Medical Imaging.

IEEE journal of biomedical and health informatics Sep 9, 2022
Federated learning is an emerging research paradigm for enabling collaboratively training deep learning models without sharing patient data. However, the data from different institutions are usually heterogeneous across institutions, which may reduce...
Deep Learning Radiography Diagnostic Imaging Humans Neural Networks, Computer
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Comprehensive review of publicly available colonoscopic imaging databases for artificial intelligence research: availability, accessibility, and usability.

Gastrointestinal endoscopy Sep 7, 2022
BACKGROUND AND AIMS: Publicly available databases containing colonoscopic imaging data are valuable resources for artificial intelligence (AI) research. Currently, little is known regarding the available number and content of these databases. This re...
Colonoscopes Radiography Colonic Polyps Artificial Intelligence Colonoscopy Humans
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Tuberculosis Detection from Chest Radiographs: Stop Training Radiologists Now.

Radiology Sep 6, 2022
Humans Radiologists Tuberculosis Deep Learning Radiography Tuberculosis, Pulmonary
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Deep Learning Detection of Active Pulmonary Tuberculosis at Chest Radiography Matched the Clinical Performance of Radiologists.

Radiology Sep 6, 2022
Background The World Health Organization (WHO) recommends chest radiography to facilitate tuberculosis (TB) screening. However, chest radiograph interpretation expertise remains limited in many regions. Purpose To develop a deep learning system (DLS)...
Sensitivity and Specificity Male Tuberculosis, Pulmonary Middle Aged Radiography, Thoracic Humans Retrospective Studies Radiography Deep Learning Female Radiologists
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Radiomics and Deep Learning for Disease Detection in Musculoskeletal Radiology: An Overview of Novel MRI- and CT-Based Approaches.

Investigative radiology Sep 1, 2022
Radiomics and machine learning-based methods offer exciting opportunities for improving diagnostic performance and efficiency in musculoskeletal radiology for various tasks, including acute injuries, chronic conditions, spinal abnormalities, and neop...
Radiography Deep Learning Magnetic Resonance Imaging Machine Learning Retrospective Studies Tomography, X-Ray Computed
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A Novel Method for COVID-19 Detection Based on DCNNs and Hierarchical Structure.

Computational and mathematical methods in medicine Aug 31, 2022
The worldwide outbreak of the new coronavirus disease (COVID-19) has been declared a pandemic by the World Health Organization (WHO). It has a devastating impact on daily life, public health, and global economy. Due to the highly infectiousness, it i...
Radiography COVID-19 Humans Deep Learning Neural Networks, Computer
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Natural Language Processing in Spine Surgery: A Systematic Review of Applications, Bias, and Reporting Transparency.

World neurosurgery Aug 30, 2022
BACKGROUND: Natural language processing (NLP) is a discipline of machine learning concerned with the analysis of language and text. Although NLP has been applied to various forms of clinical text, the applications and utility of NLP in spine surgery ...
Humans Scoliosis Radiography Magnetic Resonance Imaging PubMed Natural Language Processing
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Natural Language Processing in Radiology: Update on Clinical Applications.

Journal of the American College of Radiology : JACR Aug 25, 2022
Radiological reports are a valuable source of information used to guide clinical care and support research. Organizing and managing this content, however, frequently requires several manual curations because of the more common unstructured nature of ...
Research Report Humans Radiology Natural Language Processing Radiologists Radiography
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An automated deep learning method and novel cardiac index to detect canine cardiomegaly from simple radiography.

Scientific reports Aug 25, 2022
Since most of degenerative canine heart diseases accompany cardiomegaly, early detection of cardiac enlargement is main priority healthcare issue for dogs. In this study, we developed a new deep learning-based radiographic index quantifying canine he...
Deep Learning Retrospective Studies Dog Diseases Heart Humans Radiography Animals Cardiomegaly Dogs
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