AIMC Topic: X-Rays
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XctNet: Reconstruction network of volumetric images from a single X-ray image.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 15, 2022
Conventional Computed Tomography (CT) produces volumetric images by computing inverse Radon transformation using X-ray projections from different angles, which results in high dose radiation, long reconstruction time and artifacts. Biologically, prio...
A Principal Neighborhood Aggregation-Based Graph Convolutional Network for Pneumonia Detection.
Sensors (Basel, Switzerland)
Apr 15, 2022
Pneumonia is one of the main causes of child mortality in the world and has been reported by the World Health Organization (WHO) to be the cause of one-third of child deaths in India. Designing an automated classification system to detect pneumonia h...
COVID Detection From Chest X-Ray Images Using Multi-Scale Attention.
IEEE journal of biomedical and health informatics
Apr 14, 2022
Deep learning based methods have shown great promise in achieving accurate automatic detection of Coronavirus Disease (covid) - 19 from Chest X-Ray (cxr) images.However, incorporating explainability in these solutions remains relatively less explored...
Deep learning of chest X-rays can predict mechanical ventilation outcome in ICU-admitted COVID-19 patients.
Scientific reports
Apr 13, 2022
The COVID-19 pandemic repeatedly overwhelms healthcare systems capacity and forced the development and implementation of triage guidelines in ICU for scarce resources (e.g. mechanical ventilation). These guidelines were often based on known risk fact...
Detection of COVID-19 from CT and Chest X-ray Images Using Deep Learning Models.
Annals of biomedical engineering
Apr 12, 2022
Coronavirus 2019 (COVID-19) is a highly transmissible and pathogenic virus caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2), which first appeared in Wuhan, China, and has since spread in the whole world. This pathology has caused a ma...
COV-DLS: Prediction of COVID-19 from X-Rays Using Enhanced Deep Transfer Learning Techniques.
Journal of healthcare engineering
Apr 11, 2022
In this paper, modifications in neoteric architectures such as VGG16, VGG19, ResNet50, and InceptionV3 are proposed for the classification of COVID-19 using chest X-rays. The proposed architectures termed "COV-DLS" consist of two phases: heading mode...
Development and evaluation of machine learning models based on X-ray radiomics for the classification and differentiation of malignant and benign bone tumors.
European radiology
Apr 9, 2022
OBJECTIVES: To develop and validate machine learning models to distinguish between benign and malignant bone lesions and compare the performance to radiologists.
Accurate auto-labeling of chest X-ray images based on quantitative similarity to an explainable AI model.
Nature communications
Apr 6, 2022
The inability to accurately, efficiently label large, open-access medical imaging datasets limits the widespread implementation of artificial intelligence models in healthcare. There have been few attempts, however, to automate the annotation of such...
Pre-processing methods in chest X-ray image classification.
PloS one
Apr 5, 2022
BACKGROUND: The SARS-CoV-2 pandemic began in early 2020, paralyzing human life all over the world and threatening our security. Thus, the need for an effective, novel approach to diagnosing, preventing, and treating COVID-19 infections became paramou...
A deep learning model (FociRad) for automated detection of γ-H2AX foci and radiation dose estimation.
Scientific reports
Apr 1, 2022
DNA double-strand breaks (DSBs) are the most lethal form of damage to cells from irradiation. γ-H2AX (phosphorylated form of H2AX histone variant) has become one of the most reliable and sensitive biomarkers of DNA DSBs. However, the γ-H2AX foci assa...
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