Recent developments in segmentation of COVID-19 CT images using deep-learning: an overview of models, techniques and challenges
J Zhang, C Ying, Z Ye, D Ma, B Wang… - … Signal Processing and …, 2024 - Elsevier
The outbreak of the COVID-19 has resulted in a catastrophic situation worldwide and has
become one of the most serious diseases in the last hundred years. In recent years, with the …
become one of the most serious diseases in the last hundred years. In recent years, with the …
Real-world federated learning in radiology: hurdles to overcome and benefits to gain
MR Bujotzek, Ü Akünal, S Denner… - Journal of the …, 2025 - academic.oup.com
Abstract Objective Federated Learning (FL) enables collaborative model training while
kee** data locally. Currently, most FL studies in radiology are conducted in simulated …
kee** data locally. Currently, most FL studies in radiology are conducted in simulated …
Study on lung CT image segmentation algorithm based on threshold-gradient combination and improved convex hull method
J Zheng, L Wang, J Gui, AH Yussuf - Scientific Reports, 2024 - nature.com
Lung images often have the characteristics of strong noise, uneven grayscale distribution,
and complex pathological structures, which makes lung image segmentation a challenging …
and complex pathological structures, which makes lung image segmentation a challenging …
Relevance gradient descent for parameter optimization of image enhancement
Abstract Machine learning plays a pivotal role in constructing learning models and
leveraging abundant image data for feature extraction, which is essential for achieving …
leveraging abundant image data for feature extraction, which is essential for achieving …
MSAMS-Net: accurate lung lesion segmentation from COVID-19 CT images
Z Wang, H Zhu, X Gao - Multimedia Tools and Applications, 2024 - Springer
Abstract The coronavirus disease 2019 (COVID-19) has emerged as a global pandemic,
inflicting significant harm on the health of humans. A crucial objective in combating this …
inflicting significant harm on the health of humans. A crucial objective in combating this …
GIFNet: an effective global infection feature network for automatic COVID-19 lung lesions segmentation
Abstract The ongoing COronaVIrus Disease 2019 (COVID-19) pandemic carried by the
SARS-CoV-2 virus spread worldwide in early 2019, bringing about an existential health …
SARS-CoV-2 virus spread worldwide in early 2019, bringing about an existential health …
Using an Artificial Physarum polycephalum Colony for Threshold Image Segmentation
Z Cai, G Li, J Zhang, S **ong - Applied Sciences, 2023 - mdpi.com
Featured Application Image segmentation can be applied to image recognition and
computer vision as the most important preprocess, and the artificial Physarum polycephalum …
computer vision as the most important preprocess, and the artificial Physarum polycephalum …
COVID-19 lung infection segmentation from CT imaging using statistics and edge-region-based active contour
As of October 2024, the number of global confirmed cases of COVID-19 goes beyond 776
million, with over 7 million deaths, according to World Health Organization (WHO) website …
million, with over 7 million deaths, according to World Health Organization (WHO) website …
Semantic Lung Segmentation from Chest X-Ray Images Using Seg-Net Deep CNN Model
Implementing an accurate image segmentation to extract the lung shape from X-ray images
is a vital step in designing a CAD system that diagnoses various types of chest diseases …
is a vital step in designing a CAD system that diagnoses various types of chest diseases …
U-Net Model Combined with Ensemble Learning for Segmentation of Covid-19 Computed Tomography Images
F Atlan - 2024 9th International Conference on Computer …, 2024 - ieeexplore.ieee.org
Covid-19 CT lung segmentation has been an important area of study for researchers since
early 2020, when the Covid-19 pandemic became widespread. In the early days of the …
early 2020, when the Covid-19 pandemic became widespread. In the early days of the …