Review and classification of AI-enabled COVID-19 CT imaging models based on computer vision tasks
This article presents a systematic overview of artificial intelligence (AI) and computer vision
strategies for diagnosing the coronavirus disease of 2019 (COVID-19) using computerized …
strategies for diagnosing the coronavirus disease of 2019 (COVID-19) using computerized …
Weakly supervised segmentation of COVID19 infection with scribble annotation on CT images
Segmentation of infections from CT scans is important for accurate diagnosis and follow-up
in tackling the COVID-19. Although the convolutional neural network has great potential to …
in tackling the COVID-19. Although the convolutional neural network has great potential to …
HADCNet: Automatic segmentation of COVID-19 infection based on a hybrid attention dense connected network with dilated convolution
Y Chen, T Zhou, Y Chen, L Feng, C Zheng, L Liu… - Computers in Biology …, 2022 - Elsevier
Abstract the automatic segmentation of lung infections in CT slices provides a rapid and
effective strategy for diagnosing, treating, and assessing COVID-19 cases. However, the …
effective strategy for diagnosing, treating, and assessing COVID-19 cases. However, the …
CARes‐UNet: Content‐aware residual UNet for lesion segmentation of COVID‐19 from chest CT images
Abstract Purpose Coronavirus disease 2019 (COVID‐19) has caused a serious global
health crisis. It has been proven that the deep learning method has great potential to assist …
health crisis. It has been proven that the deep learning method has great potential to assist …
Weakly supervised segmentation of COVID-19 infection with local lesion coherence on CT images
W Sun, X Feng, J Liu, H Ma - Biomedical signal processing and control, 2023 - Elsevier
At the end of 2019, a novel coronavirus, COVID-19, was ravaging the world, wreaking havoc
on public health and the global economy. Today, although Reverse Transcription …
on public health and the global economy. Today, although Reverse Transcription …
Semi-supervised COVID-19 volumetric pulmonary lesion estimation on CT images using probabilistic active contour and CNN segmentation
Purpose A semi-supervised two-step methodology is proposed to obtain a volumetric
estimation of COVID-19-related lesions on Computed Tomography (CT) images. Methods …
estimation of COVID-19-related lesions on Computed Tomography (CT) images. Methods …
HFCF‐Net: a hybrid‐feature cross fusion network for COVID‐19 lesion segmentation from CT volumetric images
Y Wang, Q Yang, L Tian, X Zhou, I Rekik… - Medical …, 2022 - Wiley Online Library
Background The coronavirus disease 2019 (COVID‐19) spreads rapidly across the globe,
seriously threatening the health of people all over the world. To reduce the diagnostic …
seriously threatening the health of people all over the world. To reduce the diagnostic …
Weakly supervised brain tumour segmentation with label propagation and level set loss
FS Abadian‐Zadeh, MR Mohammadi… - IET Image …, 2025 - Wiley Online Library
Early diagnosis of brain tumors significantly enhances treatment success. However,
accurate detection and segmentation of tumors, essential for diagnosis, rely heavily on …
accurate detection and segmentation of tumors, essential for diagnosis, rely heavily on …