Deep supervised learning using self-adaptive auxiliary loss for COVID-19 diagnosis from imbalanced CT images.

Neurocomputing
Kai HuXieping Gao

Abstract

The outbreak and rapid spread of coronavirus disease 2019 (COVID-19) has had a huge impact on the lives and safety of people around the world. Chest CT is considered an effective tool for the diagnosis and follow-up of COVID-19. For faster examination, automatic COVID-19 diagnostic techniques using deep learning on CT images have received increasing attention. However, the number and category of existing datasets for COVID-19 diagnosis that can be used for training are limited, and the number of initial COVID-19 samples is much smaller than the normal's, which leads to the problem of class imbalance. It makes the classification algorithms difficult to learn the discriminative boundaries since the data of some classes are rich while others are scarce. Therefore, training robust deep neural networks with imbalanced data is a fundamental challenging but important task in the diagnosis of COVID-19. In this paper, we create a challenging clinical dataset (named COVID19-Diag) with category diversity and propose a novel imbalanced data classification method using deep supervised learning with a self-adaptive auxiliary loss (DSN-SAAL) for COVID-19 diagnosis. The loss function considers both the effects of data overlap between CT slices...Continue Reading

References

May 9, 2014·IEEE Transactions on Neural Networks and Learning Systems·Cristiano L Castro, Antônio P Braga
Aug 23, 2017·IEEE Transactions on Neural Networks and Learning Systems·Salman H KhanRoberto Togneri
Aug 10, 2018·Neural Networks : the Official Journal of the International Neural Network Society·Mateusz BudaMaciej A Mazurowski
Dec 10, 2019·European Journal of Nuclear Medicine and Molecular Imaging·Yu ZhaoKuangyu Shi
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Sep 22, 2020·Informatics in Medicine Unlocked·Pedro SilvaDavid Menotti
Mar 12, 2021·IEEE/ACM Transactions on Computational Biology and Bioinformatics·Ying SongYuedong Yang

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Citations

Oct 26, 2021·Neurocomputing·Madini O AlassafiReem Alotaibi

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Software Mentioned

COVIDNet
xDNN
CT
PyTorch
Trans
Contrastive
Meta
MAD
DeepPneumonia
SAAL

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