Research Article
Lung Lesion Images Classification Based on Deep Learning Model and Adaboost Techniques
@INPROCEEDINGS{10.1007/978-3-031-28816-6_8, author={Nguyen Thanh Binh and Vuong Bao Thy}, title={Lung Lesion Images Classification Based on Deep Learning Model and Adaboost Techniques}, proceedings={Context-Aware Systems and Applications. 11th EAI International Conference, ICCASA 2022, Vinh Long, Vietnam, October 27-28, 2022, Proceedings}, proceedings_a={ICCASA}, year={2023}, month={3}, keywords={Classification U-Net Lung lesion images VGG-19 Adaboost}, doi={10.1007/978-3-031-28816-6_8} }- Nguyen Thanh Binh
Vuong Bao Thy
Year: 2023
Lung Lesion Images Classification Based on Deep Learning Model and Adaboost Techniques
ICCASA
Springer
DOI: 10.1007/978-3-031-28816-6_8
Abstract
Today, the medical industry is promoting the research and application of artificial intelligence in disease diagnosis and treatment. The development of diagnostic methods with the support of electronic devices and information technology can help doctors save time in diagnosing and treating diseases, especially medical images. Diagnosis of lung lesions based on lung images is a case study. This paper proposed a method for lung lesion images classification based on modified U-Net and VGG-19 combined on adaboost techniques. The modified U-Net architecture with 5 pooling and 5 unpooling. It has the unpooling layer with kernels of size 2 × 2, stride 2 × 2 to get output consistent with the adaboost. The result of the proposed method is about 97.61% and better results than others in the Covid-19 radiography dataset.
