Chest X-ray analysis empowered with deep learning: A systematic review
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 …
particularly plays an important role in the diagnosis of medical conditions such as …
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 …
Hybrid intelligence-driven medical image recognition for remote patient diagnosis in internet of medical things
In ear of smart cities, intelligent medical image recognition technique has become a
promising way to solve remote patient diagnosis in IoMT. Although deep learning-based …
promising way to solve remote patient diagnosis in IoMT. Although deep learning-based …
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 …
A novel data augmentation-based brain tumor detection using convolutional neural network
Brain tumor is a severe cancer and a life-threatening disease. Thus, early detection is crucial
in the process of treatment. Recent progress in the field of deep learning has contributed …
in the process of treatment. Recent progress in the field of deep learning has contributed …
Deep learning in multi-class lung diseases' classification on chest X-ray images
Chest X-ray radiographic (CXR) imagery enables earlier and easier lung disease diagnosis.
Therefore, in this paper, we propose a deep learning method using a transfer learning …
Therefore, in this paper, we propose a deep learning method using a transfer learning …
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 …
A survey of deep learning for retinal blood vessel segmentation methods: taxonomy, trends, challenges and future directions
OO Sule - IEEE Access, 2022 - ieeexplore.ieee.org
Recent advancements in deep learning architectures have extended their application to
computer vision tasks, one of which is the segmentation of retinal blood vessels from retinal …
computer vision tasks, one of which is the segmentation of retinal blood vessels from retinal …
Hybrid clahe-cnn deep neural networks for classifying lung diseases from x-ray acquisitions
Chest and lung diseases are among the most serious chronic diseases in the world, and
they occur as a result of factors such as smoking, air pollution, or bacterial infection, which …
they occur as a result of factors such as smoking, air pollution, or bacterial infection, which …
[PDF][PDF] U-Net Based Chest X-ray Segmentation with Ensemble Classification for Covid-19 and Pneumonia.
K Kumarasinghe, SL Kolonne… - … Journal of Online & …, 2022 - researchgate.net
Respiratory diseases have been known to be a main cause of death worldwide. Pneumonia
and Covid-19 are two of the dominant diseases. Several deep learning based studies are …
and Covid-19 are two of the dominant diseases. Several deep learning based studies are …