| Title: | GS2-3 Detection of Lung Nodules from Temporal Subtraction CT Image Using Elastic Net-Based Features Selection |
|---|---|
| Publication: | ICAROB2025 |
| Volume: | 30 |
| Pages: | 833-836 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2025.GS2-3 |
| Author(s): | Natsuho Baba, Tohru Kamiya, Takashi Terasawa, Takatoshi Aoki |
| Publication Date: | February 13, 2025 |
| Keywords: | Computer Aided Diagnosis, Machine Learning, Temporal Subtraction Technique, Radiomics, Elastic Net |
| Abstract: | CT (computed tomography) is mainly used to diagnose lung cancer. Many CT images impose a heavy burden on visual screening, so a CAD (computer-aided diagnosis) system is expected to reduce the burden. In this paper, we propose an image analysis method to detect lung nodules from chest CT images using machine learning techniques. The best results were obtained for the method using LightGBM with feature reduction by Elastic Net. |
| PDF File: | https://alife-robotics.co.jp/members2025/icarob/data/html/data/GS/GS2/GS2-3.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
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