AIMC Topic: X-Rays

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Ensemble deep-learning networks for automated osteoarthritis grading in knee X-ray images.

Scientific reports
The Kellgren-Lawrence (KL) grading system is a scoring system for classifying the severity of knee osteoarthritis using X-ray images, and it is the standard X-ray-based grading system for diagnosing knee osteoarthritis. However, KL grading depends on...

Deep learning for report generation on chest X-ray images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Medical imaging, specifically chest X-ray image analysis, is a crucial component of early disease detection and screening in healthcare. Deep learning techniques, such as convolutional neural networks (CNNs), have emerged as powerful tools for comput...

Diagnosis and detection of pneumonia using weak-label based on X-ray images: a multi-center study.

BMC medical imaging
PURPOSE: Development and assessment the deep learning weakly supervised algorithm for the classification and detection pneumonia via X-ray.

Development and validation of open-source deep neural networks for comprehensive chest x-ray reading: a retrospective, multicentre study.

The Lancet. Digital health
BACKGROUND: Artificial intelligence (AI) systems for automated chest x-ray interpretation hold promise for standardising reporting and reducing delays in health systems with shortages of trained radiologists. Yet, there are few freely accessible AI s...

Single-Cell Radiation Response Scoring with the Deep Learning Algorithm CeCILE 2.0.

Cells
External stressors, such as ionizing radiation, have massive effects on life, survival, and the ability of mammalian cells to divide. Different types of radiation have different effects. In order to understand these in detail and the underlying mecha...

Deep Learning-based Diagnosis and Localization of Pneumothorax on Portable Supine Chest X-ray in Intensive and Emergency Medicine: A Retrospective Study.

Journal of medical systems
PURPOSE: To develop two deep learning-based systems for diagnosing and localizing pneumothorax on portable supine chest X-rays (SCXRs).

A deep learning feature extraction-based hybrid approach for detecting pediatric pneumonia in chest X-ray images.

Physical and engineering sciences in medicine
Pneumonia is a disease caused by bacteria, viruses, and fungi that settle in the alveolar sacs of the lungs and can lead to serious health complications in humans. Early detection of pneumonia is necessary for early treatment to manage and cure the d...

Phase retrieval for X-ray differential phase contrast radiography with knowledge transfer learning from virtual differential absorption model.

Computers in biology and medicine
Grating-based X-ray phase contrast radiography and computed tomography (CT) are promising modalities for future medical applications. However, the ill-posed phase retrieval problem in X-ray phase contrast imaging has hindered its use for quantitative...

Cephalometric landmark detection without X-rays combining coordinate regression and heatmap regression.

Scientific reports
Fully automated techniques using convolutional neural networks for cephalometric landmark detection have recently advanced. However, all existing studies have adopted X-rays. The problem of direct exposure of patients to X-ray radiation remains unsol...

Pulmonary abnormality screening on chest x-rays from different machine specifications: a generalized AI-based image manipulation pipeline.

European radiology experimental
BACKGROUND: Chest x-ray is commonly used for pulmonary abnormality screening. However, since the image characteristics of x-rays highly depend on the machine specifications, an artificial intelligence (AI) model developed for specific equipment usual...