[HTML][HTML] A review of deep learning in dentistry
Oral diseases have a significant impact on human health, often going unnoticed in their
early stages. Deep learning, a promising field in artificial intelligence, has shown remarkable …
early stages. Deep learning, a promising field in artificial intelligence, has shown remarkable …
Deep learning for medical image-based cancer diagnosis
Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …
diagnosis. To help readers better understand the current research status and ideas, this …
Covid-MANet: Multi-task attention network for explainable diagnosis and severity assessment of COVID-19 from CXR images
The devastating outbreak of Coronavirus Disease (COVID-19) cases in early 2020 led the
world to face health crises. Subsequently, the exponential reproduction rate of COVID-19 …
world to face health crises. Subsequently, the exponential reproduction rate of COVID-19 …
PAF-NET: A Progressive and adaptive fusion network for Pavement Crack Segmentation
L Yang, H Huang, S Kong, Y Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Automatic crack detection remains challenging due to factors such as irregular crack shapes
and sizes, uneven illumination, complex backgrounds, and image noise. Deep learning has …
and sizes, uneven illumination, complex backgrounds, and image noise. Deep learning has …
A deep segmentation network for crack detection with progressive and hierarchical context fusion
L Yang, H Huang, S Kong, Y Liu - Journal of Building Engineering, 2023 - Elsevier
Accurate detection of crack defects in infrastructure is crucial to ensure their safety and
extend their service life. However, the presence of complex backgrounds, various shapes …
extend their service life. However, the presence of complex backgrounds, various shapes …
Fractional Aquila spider monkey optimization based deep learning network for classification of brain tumor
G Nirmalapriya, V Agalya, R Regunathan… - … Signal Processing and …, 2023 - Elsevier
The tumor in the brain is a serious disease that causes death in humans. Various imaging
modalities are utilized for identifying tumors, but the huge data produced by magnetic …
modalities are utilized for identifying tumors, but the huge data produced by magnetic …
Automatic segmentation with deep learning in radiotherapy
Simple Summary Automatic segmentation of organs and other regions of interest is a
promising approach for reducing the workload of doctors in radiotherapeutic planning, but it …
promising approach for reducing the workload of doctors in radiotherapeutic planning, but it …
DRR-Net: A dense-connected residual recurrent convolutional network for surgical instrument segmentation from endoscopic images
The precise segmentation of surgical instruments is the key link for the stable and
reasonable operation of surgical robots. However, accurate surgical instrument …
reasonable operation of surgical robots. However, accurate surgical instrument …
BT-Unet: A self-supervised learning framework for biomedical image segmentation using barlow twins with U-net models
Deep learning has brought the most profound contribution towards biomedical image
segmentation to automate the process of delineation in medical imaging. To accomplish …
segmentation to automate the process of delineation in medical imaging. To accomplish …
[HTML][HTML] Investigation and benchmarking of U-Nets on prostate segmentation tasks
In healthcare, a growing number of physicians and support staff are striving to facilitate
personalized radiotherapy regimens for patients with prostate cancer. This is because …
personalized radiotherapy regimens for patients with prostate cancer. This is because …