AI Medical Compendium Topic

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X-Rays

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Machine Learning with Quantum Seagull Optimization Model for COVID-19 Chest X-Ray Image Classification.

Journal of healthcare engineering
Early and accurate detection of COVID-19 is an essential process to curb the spread of this deadly disease and its mortality rate. Chest radiology scan is a significant tool for early management and diagnosis of COVID-19 since the virus targets the r...

Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoost.

Radiography (London, England : 1995)
INTRODUCTION: In late 2019 and after the COVID-19 pandemic in the world, many researchers and scholars tried to provide methods for detecting COVID-19 cases. Accordingly, this study focused on identifying patients with COVID-19 from chest X-ray image...

A fully automated sex estimation for proximal femur X-ray images through deep learning detection and classification.

Legal medicine (Tokyo, Japan)
PURPOSE: To develop a fully automated deep learning pipeline using digital radiographs to detect the proximal femur region for accurate automated sex estimation.

Improving convolutional neural network learning based on a hierarchical bezier generative model for stenosis detection in X-ray images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automatic detection of stenosis on X-ray Coronary Angiography (XCA) images may help diagnose early coronary artery disease. Stenosis is manifested by a buildup of plaque in the arteries, decreasing the blood flow to the hear...

A ensemble methodology for automatic classification of chest X-rays using deep learning.

Computers in biology and medicine
Chest radiographies, or chest X-rays, are the most standard imaging exams used in daily hospitals. Responsible for assisting in detecting numerous pathologies and findings that directly interfere in the patient's life, this exam is therefore crucial ...

Semisolid Pharmaceutical Product Characterization Using Non-invasive X-ray Microscopy and AI-Based Image Analytics.

The AAPS journal
This work reports the use of X-ray microscopy (XRM) imaging to characterize the microstructure of semisolid formulations containing multiple immiscible phases. For emulsion-based semisolid formulations, the disperse phase globule size and its distrib...

Learning-based occupational x-ray scatter estimation.

Physics in medicine and biology
During x-ray-guided interventional procedures, the medical staff is exposed to scattered ionizing radiation caused by the patient. To increase the staff's awareness of the invisible radiation and monitor dose online, computational scatter estimation ...

Deep learning-based 2D/3D registration of an atlas to biplanar X-ray images.

International journal of computer assisted radiology and surgery
PURPOSE: The registration of a 3D atlas image to 2D radiographs enables 3D pre-operative planning without the need to acquire costly and high-dose CT-scans. Recently, many deep-learning-based 2D/3D registration methods have been proposed which tackle...

A radiomics-boosted deep-learning model for COVID-19 and non-COVID-19 pneumonia classification using chest x-ray images.

Medical physics
PURPOSE: To develop a deep learning model design that integrates radiomics analysis for enhanced performance of COVID-19 and non-COVID-19 pneumonia detection using chest x-ray images.

Deep Learning-Based Computer-Aided Pneumothorax Detection Using Chest X-ray Images.

Sensors (Basel, Switzerland)
Pneumothorax is a thoracic disease leading to failure of the respiratory system, cardiac arrest, or in extreme cases, death. Chest X-ray (CXR) imaging is the primary diagnostic imaging technique for the diagnosis of pneumothorax. A computerized diagn...