Advances in deep learning for tuberculosis screening using chest X-rays: the last 5 years review
There has been an explosive growth in research over the last decade exploring machine
learning techniques for analyzing chest X-ray (CXR) images for screening cardiopulmonary …
learning techniques for analyzing chest X-ray (CXR) images for screening cardiopulmonary …
A systematic review of the diagnostic accuracy of artificial intelligence-based computer programs to analyze chest x-rays for pulmonary tuberculosis
M Harris, A Qi, L Jeagal, N Torabi, D Menzies… - PloS one, 2019 - journals.plos.org
We undertook a systematic review of the diagnostic accuracy of artificial intelligence-based
software for identification of radiologic abnormalities (computer-aided detection, or CAD) …
software for identification of radiologic abnormalities (computer-aided detection, or CAD) …
Truncated inception net: COVID-19 outbreak screening using chest X-rays
Abstract Since December 2019, the Coronavirus Disease (COVID-19) pandemic has caused
world-wide turmoil in a short period of time, and the infection, caused by SARS-CoV-2, is …
world-wide turmoil in a short period of time, and the infection, caused by SARS-CoV-2, is …
Efficient deep network architectures for fast chest X-ray tuberculosis screening and visualization
Automated diagnosis of tuberculosis (TB) from chest X-Rays (CXR) has been tackled with
either hand-crafted algorithms or machine learning approaches such as support vector …
either hand-crafted algorithms or machine learning approaches such as support vector …
Deep features to detect pulmonary abnormalities in chest X-rays due to infectious diseaseX: Covid-19, pneumonia, and tuberculosis
Chest X-ray (CXR) imaging is a low-cost, easy-to-use imaging alternative that can be used
to diagnose/screen pulmonary abnormalities due to infectious diseaseX: Covid-19 …
to diagnose/screen pulmonary abnormalities due to infectious diseaseX: Covid-19 …
Visualization and interpretation of convolutional neural network predictions in detecting pneumonia in pediatric chest radiographs
Pneumonia affects 7% of the global population, resulting in 2 million pediatric deaths every
year. Chest X-ray (CXR) analysis is routinely performed to diagnose the disease. Computer …
year. Chest X-ray (CXR) analysis is routinely performed to diagnose the disease. Computer …
Triple attention learning for classification of 14 thoracic diseases using chest radiography
Chest X-ray is the most common radiology examinations for the diagnosis of thoracic
diseases. However, due to the complexity of pathological abnormalities and lack of detailed …
diseases. However, due to the complexity of pathological abnormalities and lack of detailed …
Ensemble learning based automatic detection of tuberculosis in chest X-ray images using hybrid feature descriptors
Tuberculosis (TB) remains one of the major health problems in modern times with a high
mortality rate. While efforts are being made to make early diagnosis accessible and more …
mortality rate. While efforts are being made to make early diagnosis accessible and more …
A review on lung boundary detection in chest X-rays
Purpose Chest radiography is the most common imaging modality for pulmonary diseases.
Due to its wide usage, there is a rich literature addressing automated detection of …
Due to its wide usage, there is a rich literature addressing automated detection of …
Feature selection for automatic tuberculosis screening in frontal chest radiographs
To detect pulmonary abnormalities such as Tuberculosis (TB), an automatic analysis and
classification of chest radiographs can be used as a reliable alternative to more …
classification of chest radiographs can be used as a reliable alternative to more …