Classifiers Combined with DenseNet Models for Lung Cancer Computed Tomography Image Classification: A Comparative Analysis
This evaluation demonstrates the effectiveness of combining DenseNet architectures with different classifiers for lung cancer CT classification. The MLP-DenseNet-169 achieved optimal performance, while SVM-DenseNet-169 showed superior stability, providing valuable benchmarks for automated lung cancer detection systems.
Authors
- Shuya Liu (ORCID: https://orcid.org/0000-0001-6897-036X)
- Ruihua Su
- Menna Allah Mahmoud (ORCID: https://orcid.org/0000-0003-4329-2405)
- Sijun Wu (ORCID: https://orcid.org/0000-0003-2764-4618)
- Yanhua Wen
- Yubao Guan
Institutions
- Guangzhou Medical University (CN)
Publication Details
- Journal
- Current Medical Imaging Formerly Current Medical Imaging Reviews
- Published
- 2025-08-28
- DOI
- https://doi.org/10.2174/0115734056399377250818100506
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00