[HTML][HTML] Machine and deep learning for tuberculosis detection on chest x-rays: systematic literature review
Background Tuberculosis (TB) was the leading infectious cause of mortality globally prior to
COVID-19 and chest radiography has an important role in the detection, and subsequent …
COVID-19 and chest radiography has an important role in the detection, and subsequent …
A comprehensive review on advancement in deep learning techniques for automatic detection of tuberculosis from chest X-ray images
E Kotei, R Thirunavukarasu - Archives of Computational Methods in …, 2024 - Springer
Tuberculosis is an infectious disease caused by a widely spread microbe called
Mycobacterium tuberculosis (MTB). Tuberculosis (TB) detection with chest x-ray images is …
Mycobacterium tuberculosis (MTB). Tuberculosis (TB) detection with chest x-ray images is …
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 …
Classification of skin cancer from dermoscopic images using deep neural network architectures
A powerful medical decision support system for classifying skin lesions from dermoscopic
images is an important tool to prognosis of skin cancer. In the recent years, Deep …
images is an important tool to prognosis of skin cancer. In the recent years, Deep …
[Retracted] Enhance‐Net: An Approach to Boost the Performance of Deep Learning Model Based on Real‐Time Medical Images
V Narayan, PK Mall, A Alkhayyat, K Abhishek… - Journal of …, 2023 - Wiley Online Library
Real‐time medical image classification is a complex problem in the world. Using IoT
technology in medical applications assures that the healthcare sectors improve the quality of …
technology in medical applications assures that the healthcare sectors improve the quality of …
A multichannel EfficientNet deep learning-based stacking ensemble approach for lung disease detection using chest X-ray images
This paper proposes a multichannel deep learning approach for lung disease detection
using chest X-rays. The multichannel models used in this work are EfficientNetB0 …
using chest X-rays. The multichannel models used in this work are EfficientNetB0 …
Segmentation and classification on chest radiography: a systematic survey
T Agrawal, P Choudhary - The Visual Computer, 2023 - Springer
Chest radiography (X-ray) is the most common diagnostic method for pulmonary disorders.
A trained radiologist is required for interpreting the radiographs. But sometimes, even …
A trained radiologist is required for interpreting the radiographs. But sometimes, even …
Deep pre-trained networks as a feature extractor with XGBoost to detect tuberculosis from chest X-ray
M Rahman, Y Cao, X Sun, B Li, Y Hao - Computers & Electrical Engineering, 2021 - Elsevier
Pulmonary Tuberculosis is a plague caused by Mycobacterium tuberculosis or Tubercle
bacillus, which kills 1.8 million people worldwide. Tuberculosis is among the top 10 deadly …
bacillus, which kills 1.8 million people worldwide. Tuberculosis is among the top 10 deadly …
Tuberculosis chest X-ray detection using CNN-based hybrid segmentation and classification approach
Tuberculosis still significantly impacts the world's population, with more than 10 million
people getting sick each year. Researchers have focused on developing computer-aided …
people getting sick each year. Researchers have focused on developing computer-aided …
Lung-GANs: unsupervised representation learning for lung disease classification using chest CT and X-ray images
Lung diseases are a tremendous challenge to the health and life of people globally,
accounting for 5 out of 30 most common causes of death. Early diagnosis is crucial to help in …
accounting for 5 out of 30 most common causes of death. Early diagnosis is crucial to help in …