Semi-supervised COVID-19 CT image segmentation using deep generative models.

Judah ZammitDaryl L X FungQian LiuCarson Kai-Sang LeungPingzhao Hu

Published in: BMC bioinformatics (2022)

We compare StitchNet to other image segmentation models on a high-quality dataset of CT images from COVID-19 patients. We show that our model has comparable performance to the other segmentation models. We also explore the potential limitations and advantages in our proposed algorithm and propose some potential future research directions for this challenging issue.

Keyphrases

deep learning
convolutional neural network
machine learning
sars cov
computed tomography
image quality
coronavirus disease
dual energy
contrast enhanced
positron emission tomography
magnetic resonance imaging
climate change
optical coherence tomography
respiratory syndrome coronavirus