AIMC Topic: Radiography

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The Delta Robot-A long travel nano-positioning stage for scanning x-ray microscopy.

The Review of scientific instruments Apr 1, 2022
A new stage design concept, the Delta Robot, is presented, which is a parallel kinematic design for scanning x-ray microscopy applications. The stage employs three orthogonal voice coils, which actuate parallelogram flexures. The design has a 3 mm tr...
X-Rays Radiography Microscopy Computer Simulation Robotics
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Quality use of artificial intelligence in medical imaging: What do radiologists need to know?

Journal of medical imaging and radiation oncology Mar 1, 2022
The application of artificial intelligence, and in particular machine learning, to the practice of radiology, is already impacting the quality of imaging care. It will increasingly do so in the future. Radiologists need to be aware of factors that go...
Humans Radiology Radiologists Artificial Intelligence Machine Learning Radiography
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[Promoting the application of federated learning in medical imaging artificial intelligence].

Zhonghua yi xue za zhi Feb 8, 2022
Medical image-based artificial intelligence (AI) systems have shown great potential in assisting disease diagnosis and treatment. However, the challenges, such as data silos, privacy security and standardization, seriously impedes the application of ...
Diagnostic Imaging Artificial Intelligence Radiography
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Estimation of patient's angle from skull radiographs using deep learning.

Journal of X-ray science and technology Jan 1, 2022
BACKGROUND: Skull radiography, an assessment method for initial diagnosis and post-operative follow-up, requires substantial retaking of various types of radiographs. During retaking, a radiologic technologist estimates a patient's rotation angle fro...
Radiography Head Neural Networks, Computer Humans Skull Deep Learning
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Artificial Intelligence in Radiology: an introduction to the most important concepts.

Radiologia Jan 1, 2022
The interpretation of medical imaging tests is one of the main tasks that radiologists do. For years, it has been a challenge to teach computers to do this kind of cognitive task; the main objective of the field of computer vision is to overcome this...
Humans Radiology Radiologists Artificial Intelligence Radiography
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Optimized chest X-ray image semantic segmentation networks for COVID-19 early detection.

Journal of X-ray science and technology Jan 1, 2022
BACKGROUND: Although detection of COVID-19 from chest X-ray radiography (CXR) images is faster than PCR sputum testing, the accuracy of detecting COVID-19 from CXR images is lacking in the existing deep learning models.
Humans Deep Learning Semantics Radiography COVID-19 X-Rays SARS-CoV-2
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Use of deep learning methods for hand fracture detection from plain hand radiographs.

Ulusal travma ve acil cerrahi dergisi = Turkish journal of trauma & emergency surgery : TJTES Jan 1, 2022
BACKGROUND: Patients with hand trauma are usually examined in emergency departments of hospitals. Hand fractures are frequently observed in patients with hand trauma. Here, we aim to develop a computer-aided diagnosis (CAD) method to assist physician...
Hand Humans Fractures, Bone Neural Networks, Computer Radiography Deep Learning
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[Evaluation of Radiograph Accuracy in Skull X-ray Images Using Deep Learning].

Nihon Hoshasen Gijutsu Gakkai zasshi Jan 1, 2022
PURPOSE: Accurate positioning is essential for radiography, and it is especially important to maintain image reproducibility in follow-up observations. The decision on re-taking radiographs is entrusting to the individual radiological technologist. T...
Reproducibility of Results Deep Learning Radiography Skull X-Rays
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Demographic Reporting in Publicly Available Chest Radiograph Data Sets: Opportunities for Mitigating Sex and Racial Disparities in Deep Learning Models.

Journal of the American College of Radiology : JACR Jan 1, 2022
OBJECTIVE: Data sets with demographic imbalances can introduce bias in deep learning models and potentially amplify existing health disparities. We evaluated the reporting of demographics and potential biases in publicly available chest radiograph (C...
Ethnicity Male Deep Learning Radiography Bias Humans Female
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Detecting Racial/Ethnic Health Disparities Using Deep Learning From Frontal Chest Radiography.

Journal of the American College of Radiology : JACR Jan 1, 2022
PURPOSE: The aim of this study was to assess racial/ethnic and socioeconomic disparities in the difference between atherosclerotic vascular disease prevalence measured by a multitask convolutional neural network (CNN) deep learning model using fronta...
Ethnicity Social Deprivation Carcinoma, Hepatocellular Radiography Retrospective Studies SARS-CoV-2 Deep Learning Liver Neoplasms Humans COVID-19
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