Detection of Lung Nodules from Temporal Subtraction CT Image Using Elastic Net-Based Features Selection

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.

Authors

Institutions

Publication Details

Journal
Proceedings of International Conference on Artificial Life and Robotics
Published
2025-02-13
DOI
https://doi.org/10.5954/icarob.2025.gs2-3
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
1.06
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Detection of Lung Nodules from Temporal Subtraction CT Image Using Elastic Net-Based Features Selection

Takatoshi Aoki, Tohru Kamiya, Natsuho Baba, Takashi Terasawa
1 citations
Proceedings of International Conference on Artificial Life and Robotics
Radiomics and Machine Learning in Medical Imaging
1.06
article

Detection of Lung Nodules from Temporal Subtraction CT Image Using Elastic Net-Based Features Selection

Takatoshi Aoki, Tohru Kamiya, Natsuho Baba, Takashi Terasawa
article en
1 citations

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.

Proceedings of International Conference on Artificial Life and RoboticsVol. 30
University of Occupational and Environmental Health Japan (JP), Kyushu Institute of Technology (JP)
Reduced inequalities
Openalex Percentile: Top 24%
Radiomics and Machine Learning in Medical Imaging
1.06
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.