AIMC Topic: X-Rays

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Accuracy of deep learning for automated detection of pneumonia using chest X-Ray images: A systematic review and meta-analysis.

Computers in biology and medicine
BACKGROUND: Recently, deep learning (DL) algorithms have received widespread popularity in various medical diagnostics. This study aimed to evaluate the diagnostic performance of DL models in the detection and classifying of pneumonia using chest X-r...

Deep convolutional neural network-based anomaly detection for organ classification in gastric X-ray examination.

Computers in biology and medicine
AIM: The aim of this study was to determine whether our deep convolutional neural network-based anomaly detection model can distinguish differences in esophagus images and stomach images obtained from gastric X-ray examinations.

Deep learning based spectral extrapolation for dual-source, dual-energy x-ray computed tomography.

Medical physics
PURPOSE: Data completion is commonly employed in dual-source, dual-energy computed tomography (CT) when physical or hardware constraints limit the field of view (FoV) covered by one of two imaging chains. Practically, dual-energy data completion is a...

Pneumonia Detection in Chest X-Ray Dose-Equivalent CT: Impact of Dose Reduction on Detectability by Artificial Intelligence.

Academic radiology
RATIONALE AND OBJECTIVES: There has been a significant increase of immunocompromised patients in recent years due to new treatment modalities for previously fatal diseases. This comes at the cost of an elevated risk for infectious diseases, most nota...

New machine learning method for image-based diagnosis of COVID-19.

PloS one
COVID-19 is a worldwide epidemic, as announced by the World Health Organization (WHO) in March 2020. Machine learning (ML) methods can play vital roles in identifying COVID-19 patients by visually analyzing their chest x-ray images. In this paper, a ...

Explainable Deep Learning for Pulmonary Disease and Coronavirus COVID-19 Detection from X-rays.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Coronavirus disease (COVID-19) is an infectious disease caused by a new virus never identified before in humans. This virus causes respiratory disease (for instance, flu) with symptoms such as cough, fever and, in severe cas...

Understanding spatial language in radiology: Representation framework, annotation, and spatial relation extraction from chest X-ray reports using deep learning.

Journal of biomedical informatics
Radiology reports contain a radiologist's interpretations of images, and these images frequently describe spatial relations. Important radiographic findings are mostly described in reference to an anatomical location through spatial prepositions. Suc...

Evaluation of deep learning detection and classification towards computer-aided diagnosis of breast lesions in digital X-ray mammograms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Deep learning detection and classification from medical imagery are key components for computer-aided diagnosis (CAD) systems to efficiently support physicians leading to an accurate diagnosis of breast lesions.

Dose image prediction for range and width verifications from carbon ion-induced secondary electron bremsstrahlung x-rays using deep learning workflow.

Medical physics
PURPOSE: Imaging of the secondary electron bremsstrahlung (SEB) x rays emitted during particle-ion irradiation is a promising method for beam range estimation. However, the SEB x-ray images are not directly correlated to the dose images. In addition,...

Using X-ray images and deep learning for automated detection of coronavirus disease.

Journal of biomolecular structure & dynamics
Coronavirus is still the leading cause of death worldwide. There are a set number of COVID-19 test units accessible in emergency clinics because of the expanding cases daily. Therefore, it is important to implement an automatic detection and classifi...