scholarly journals Automatic detection of pneumonia in chest X-rays using Lobe deep residual network

2021 ◽  
Author(s):  
Daniel Kvak ◽  
Karolína Kvaková
Keyword(s):  
Early Detection ◽  
Viral Infection ◽  
Chest Radiography ◽  
Lung Diseases ◽  
Supervised Classification ◽  
Bacterial Disease ◽  
X Rays ◽  
Binary Classifier ◽  
Reliability Of Results ◽  
Residual Network

One of the critical tools for early detection and subsequent evaluation of the incidence of lung diseases is chest radiography. At a time when the speed and reliability of results, especially for COVID-19 positive patients, is important, the development of applications that would facilitate the work of untrained staff involved in the evaluation is also crucial. Our model takes the form of a simple and intuitive application, into which you only need to upload X-rays: tens or hundreds at once. In just a few seconds, the physician will determine the patient's diagnosis, including the percentage accuracy of the estimate. While the original idea was a mere binary classifier that could tell if a patient was suffering from pneumonia or not, in this paper we present a model that distinguishes between a bacterial disease, a viral infection, or a finding caused by COVID-19. The aim of this research is to demonstrate whether pneumonia can be detected or even spatially localized using a uniform, supervised classification.

scholarly journals Interpretable multi-stream ensemble learning for radiographic pattern recognition

2021 ◽  
Author(s):  
Jose Raniery Ferreira ◽  
Diego Armando Cardona Cardenas
Keyword(s):  
Neural Networks ◽  
Pattern Recognition ◽  
Early Detection ◽  
Ensemble Learning ◽  
Chest Radiography ◽  
Lung Diseases ◽  
Model Output ◽  
Critical Factors ◽  
Ensemble Strategy ◽  
Computer Based

Chest radiography (CXR) remains an essential component to evaluate lung diseases. However, it is crucial nowadays to include computer-based tools to aid physicians in the early detection of chest abnormalities. Therefore, this work proposed deep ensemble models to improve the CXR evaluation, interpretability, and reproducibility. Five convolutional neural networks and six different processed image inputs yielded an AUC of 0.982. Furthermore, ensemble learning could produce more reliable outcomes as it did not consider the information of only one method. Moreover, the ensemble strategy balanced the most critical factors from each model to perform a more consistent classification. Finally, class activation and gradient propagation maps allowed locally visualizing CXR regions that most activate neurons from the trained models and explaining practically which areas of the CXR correlated to the model output.

scholarly journals Early Detection Methods for Silicosis in Australia and Internationally: A Review of the Literature

2021 ◽  
Vol 18 (15) ◽  
pp. 8123
Author(s):  
Emma K. Austin ◽  
Carole James ◽  
John Tessier
Keyword(s):  
Early Detection ◽  
Literature Review ◽  
Detection Method ◽  
Detection Methods ◽  
X Rays ◽  
Review Of The Literature ◽  
Occupational Lung Disease ◽  
Work Related ◽  
Growing Body ◽  
Future Work

Pneumoconiosis, or occupational lung disease, is one of the world’s most prevalent work-related diseases. Silicosis, a type of pneumoconiosis, is caused by inhaling respirable crystalline silica (RCS) dust. Although silicosis can be fatal, it is completely preventable. Hundreds of thousands of workers globally are at risk of being exposed to RCS at the workplace from various activities in many industries. Currently, in Australia and internationally, there are a range of methods used for the respiratory surveillance of workers exposed to RCS. These methods include health and exposure questionnaires, spirometry, chest X-rays, and HRCT. However, these methods predominantly do not detect the disease until it has significantly progressed. For this reason, there is a growing body of research investigating early detection methods for silicosis, particularly biomarkers. This literature review summarises the research to date on early detection methods for silicosis and makes recommendations for future work in this area. Findings from this review conclude that there is a critical need for an early detection method for silicosis, however, further laboratory- and field-based research is required.

Chest X-Ray Refresher

2014 ◽  
pp. 379-389
Author(s):  
Christopher H. Fanta
Keyword(s):  
Lung Diseases ◽  
Interstitial Lung Diseases ◽  
X Rays ◽  
X Ray ◽  
Obstructive Lung Diseases ◽  
Chest X Ray

This Chest X-Ray Refresher is organized as a game. For each of the three topics to be discussed, we offer four chest x-rays and four clinical histories. The order of each set is random. The exercise asks that you consider the clues in the history and the findings on chest x-ray to match the history with the x-ray. In many instances, the combination will suggest a diagnosis or a limited differential of diagnostic possibilities. The three topics to be discussed are hemoptysis, chronic interstitial lung diseases, and obstructive lung diseases.

scholarly journals EARLY DETECTION OF BREAST CANCER SAVES LIFE: A REVIEW OF MICROWAVE IMAGING AGAINST X-RAYS MAMMOGRAPHY

2019 ◽  
pp. 326-343
Author(s):  
Maryam Liaqat ◽  
Ali Raza ◽  
Saher Jabeen ◽  
Ramiza Ali ◽  
Sobia Kanwal ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Early Detection ◽  
Microwave Imaging ◽  
X Rays

scholarly journals The Crucial Role of NLRP3 Inflammasome in Viral Infection-Associated Fibrosing Interstitial Lung Diseases

2021 ◽  
Vol 22 (19) ◽  
pp. 10447
Author(s):  
Wiwin Is Effendi ◽  
Tatsuya Nagano
Keyword(s):  
Viral Infection ◽  
Nlrp3 Inflammasome ◽  
Lung Diseases ◽  
Alveolar Epithelium ◽  
Interstitial Lung Diseases ◽  
Molecular Signaling ◽  
Intrinsic Factors ◽  
Matrix Deposition ◽  
Age Related

Idiopathic pulmonary fibrosis (IPF), one of the most common fibrosing interstitial lung diseases (ILD), is a chronic-age-related respiratory disease that rises from repeated micro-injury of the alveolar epithelium. Environmental influences, intrinsic factors, genetic and epigenetic risk factors that lead to chronic inflammation might be implicated in the development of IPF. The exact triggers that initiate the fibrotic response in IPF remain enigmatic, but there is now increasing evidence supporting the role of chronic exposure of viral infection. During viral infection, activation of the NLRP3 inflammasome by integrating multiple cellular and molecular signaling implicates robust inflammation, fibroblast proliferation, activation of myofibroblast, matrix deposition, and aberrant epithelial-mesenchymal function. Overall, the crosstalk of the NLRP3 inflammasome and viruses can activate immune responses and inflammasome-associated molecules in the development, progression, and exacerbation of IPF.

Automated chest radiography and mass systematic screening for tuberculosis

2020 ◽  
Vol 24 (7) ◽  
pp. 665-673 ◽  
Author(s):  
F. Madhani ◽  
R. A. Maniar ◽  
A. Burfat ◽  
M. Ahmed ◽  
S. Farooq ◽  
...  
Keyword(s):  
Chest Radiography ◽  
Strong Association ◽  
Diagnostic Testing ◽  
X Rays ◽  
Computer Aided Detection ◽  
Data Collection Tool ◽  
Systematic Screening ◽  
X Ray ◽  
Detection Software ◽  
Using Data

BACKGROUND: Systematic screening for TB using automated chest radiography (ACR) with computer-aided detection software (CAD4TB) has been implemented at scale in Karachi, Pakistan. Despite evidence supporting the use of ACR as a pre-screen prior to Xpert® MTB/RIF diagnostic testing in presumptive TB patients, there has been no data published on its use in mass screening in real-world settings.METHOD: Screening was undertaken using mobile digital X-ray vehicles at hospital facilities and community camps. Chest X-rays were offered to individuals aged ≥15 years, regardless of symptoms. Those with a CAD4TB score of ≥70 were offered Xpert testing. The association between Xpert positivity and CAD4TB scores was examined using data collected between 1 January and 30 June 2018 using a custom-built data collection tool.RESULTS: Of the 127 062 individuals screened, 97.2% had a valid CAD4TB score; 11 184 (9.1%) individuals had a CAD4TB score ≥70. Prevalence of Xpert positivity rose from 0.7% in the <50 category to 23.5% in the >90 category. The strong linear association between CAD4TB score and Xpert positivity was found in both community and hospital settings.CONCLUSION: The strong association between CAD4TB scores and Xpert positivity provide evidence that an ACR-based pre-screening performs well when implemented at scale in a high-burden setting.

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