Chest X-ray analysis empowered with deep learning: A systematic review

D Meedeniya, H Kumarasinghe, S Kolonne… - Applied Soft …, 2022 - Elsevier
Chest radiographs are widely used in the medical domain and at present, chest X-radiation
particularly plays an important role in the diagnosis of medical conditions such as …

Reliable tuberculosis detection using chest X-ray with deep learning, segmentation and visualization

T Rahman, A Khandakar, MA Kadir, KR Islam… - Ieee …, 2020 - ieeexplore.ieee.org
Tuberculosis (TB) is a chronic lung disease that occurs due to bacterial infection and is one
of the top 10 leading causes of death. Accurate and early detection of TB is very important …

Intelligent pneumonia identification from chest x-rays: A systematic literature review

W Khan, N Zaki, L Ali - IEEE Access, 2021 - ieeexplore.ieee.org
Chest radiography is a significant diagnostic tool used to detect diseases afflicting the chest.
The automatic detection techniques associated with computer vision are being adopted in …

Advanced meta-heuristics, convolutional neural networks, and feature selectors for efficient COVID-19 X-ray chest image classification

ESM El-Kenawy, S Mirjalili, A Ibrahim… - Ieee …, 2021 - ieeexplore.ieee.org
The chest X-ray is considered a significant clinical utility for basic examination and
diagnosis. The human lung area can be affected by various infections, such as bacteria and …

Enhanced lung image segmentation using deep learning

S Gite, A Mishra, K Kotecha - Neural Computing and Applications, 2023 - Springer
With the advances in technology, assistive medical systems are emerging with rapid growth
and hel** healthcare professionals. The proactive diagnosis of diseases with artificial …

Classification and detection of COVID-19 X-Ray images based on DenseNet and VGG16 feature fusion

L Kong, J Cheng - Biomedical Signal Processing and Control, 2022 - Elsevier
Since December 2019, the novel coronavirus disease (COVID-19) caused by the syndrome
coronavirus 2 (SARS-CoV-2) strain has spread widely around the world and has become a …

A rapid, accurate and machine-agnostic segmentation and quantification method for CT-based COVID-19 diagnosis

L Zhou, Z Li, J Zhou, H Li, Y Chen… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
COVID-19 has caused a global pandemic and become the most urgent threat to the entire
world. Tremendous efforts and resources have been invested in develo** diagnosis …

Benchmarking methodology for selection of optimal COVID-19 diagnostic model based on entropy and TOPSIS methods

MA Mohammed, KH Abdulkareem, AS Al-Waisy… - Ieee …, 2020 - ieeexplore.ieee.org
Nowadays, coronavirus (COVID-19) is getting international attention due it considered as a
life-threatened epidemic disease that hard to control the spread of infection around the …

Artificial intelligence-enabled Internet of Things-based system for COVID-19 screening using aerial thermal imaging

A Barnawi, P Chhikara, R Tekchandani… - Future Generation …, 2021 - Elsevier
Abstract Internet of Things (IoT) has recently brought an influential research and analysis
platform in a broad diversity of academic and industrial disciplines, particularly in healthcare …

A multichannel EfficientNet deep learning-based stacking ensemble approach for lung disease detection using chest X-ray images

V Ravi, V Acharya, M Alazab - Cluster Computing, 2023 - Springer
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 …