Classic Augmentation based Classifier Generative Adversarial Network (CACGAN) for COVID-19 diagnosis

Haodong Li

doi:10.1117/12.2668115

28 March 2023 Classic Augmentation based Classifier Generative Adversarial Network (CACGAN) for COVID-19 diagnosis

Haodong Li

Proceedings Volume 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022); 125663X (2023) https://doi.org/10.1117/12.2668115
Event: Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 2022, Chongqing, China

Abstract

Computer-aided diagnosis of COVID-19 from lung medical images has received increasing attention in previous clinical practice and research. However, developing such automatic model is usually challenging due to the requirement of a large amount of data and sufficient computer power. With only 317 training images, this paper presents a Classic Augmentation based Classifier Generative Adversarial Network (CACGAN) for data synthetising. In order to take into account, the feature extraction ability and lightness of the model for lung CT images, the CACGAN network is mainly constructed by convolution blocks. During the training process, each iteration will update the discriminator's network parameters twice and the generator's network parameters once. For the evaluation of CACGAN, this paper organized multiple comparison between each pair from CACGAN synthetic data, classic augmented data, and original data. In this paper, seven classifiers are built, ranging from simple to complex, and are trained for the three sets of data respectively. To control the variable, the three sets of data use the exact same classifier structure and the exact same validation dataset. The result shows the CACGAN successfully learned how to synthesize new lung CT images with specific labels.

Citation Download Citation

Haodong Li "Classic Augmentation based Classifier Generative Adversarial Network (CACGAN) for COVID-19 diagnosis", Proc. SPIE 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 125663X (28 March 2023); https://doi.org/10.1117/12.2668115

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KEYWORDS

Data modeling

Lung

Convolution

COVID 19

Histograms

Image processing

Image segmentation

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