A survey on artificial intelligence in pulmonary imaging
Over the last decade, deep learning (DL) has contributed to a paradigm shift in computer
vision and image recognition creating widespread opportunities of using artificial …
vision and image recognition creating widespread opportunities of using artificial …
Dung beetle optimization with deep feature fusion model for lung cancer detection and classification
Simple Summary Medical imaging devices can be vital in primary-stage lung tumor analysis
and the observation of lung tumors from the treatment. Many medical imaging modalities like …
and the observation of lung tumors from the treatment. Many medical imaging modalities like …
StackGridCov: a robust stacking ensemble learning-based model integrated with GridSearchCV hyperparameter tuning technique for mutation prediction of COVID-19 …
The emergence of the coronavirus disease 2019 (COVID-19) pandemic has caused great
fear and panic around the world. In order to fight the COVID-19 virus, countries have had to …
fear and panic around the world. In order to fight the COVID-19 virus, countries have had to …
DMFL_Net: A federated learning-based framework for the classification of COVID-19 from multiple chest diseases using X-rays
Coronavirus Disease 2019 (COVID-19) is still a threat to global health and safety, and it is
anticipated that deep learning (DL) will be the most effective way of detecting COVID-19 and …
anticipated that deep learning (DL) will be the most effective way of detecting COVID-19 and …
Detailed-based dictionary learning for low-light image enhancement using camera response model for industrial applications
Images captured in low-light environments are severely degraded due to insufficient light,
which causes the performance decline of both commercial and consumer devices. One of …
which causes the performance decline of both commercial and consumer devices. One of …
Emerging Technologies in the Field of Smart Monitoring Healthcare System with Cardiac Disease
The genesis and spread of illnesses have become a serious problem in the ever-expanding
world of innovation and evolution. Technology-assisted precaution, disease control, and …
world of innovation and evolution. Technology-assisted precaution, disease control, and …
Unsupervised and quantitative intestinal ischemia detection using conditional adversarial network in multimodal optical imaging
Y Wang, L Tiusaba, S Jacobs… - Journal of Medical …, 2022 - spiedigitallibrary.org
Purpose Intraoperative evaluation of bowel perfusion is currently dependent upon subjective
assessment. Thus, quantitative and objective methods of bowel viability in intestinal …
assessment. Thus, quantitative and objective methods of bowel viability in intestinal …
[PDF][PDF] Medical image fusion based on anisotropic diffusion and non-subsampled contourlet transform
The synthesis of visual information from multiple medical imaging inputs to a single fused
image without any loss of detail and distortion is known as multimodal medical image fusion …
image without any loss of detail and distortion is known as multimodal medical image fusion …
Automated quantitative lung CT improves prognostication in non-ICU COVID-19 patients beyond conventional biomarkers of disease
P Palumbo, MM Palumbo, F Bruno, G Picchi… - Diagnostics, 2021 - mdpi.com
(1) Background: COVID-19 continues to represent a worrying pandemic. Despite the high
percentage of non-severe illness, a wide clinical variability is often reported in real-world …
percentage of non-severe illness, a wide clinical variability is often reported in real-world …
Analysis of COVID-19 outbreak in Hubei province based on Tencent's location big data
L Hua, R Ran, T Li - Frontiers in Public Health, 2023 - frontiersin.org
Rapid urbanization has gradually strengthened the spatial links between cities, which
greatly aggravates the possibility of the spread of an epidemic. Traditional methods lack the …
greatly aggravates the possibility of the spread of an epidemic. Traditional methods lack the …