The influence of image selection and segmentation on the extraction of lung cancer imaging radiomics features using 3D-Slicer software
The enhancement of lung CT has a relatively small impact on extracting image features, while selecting lung or mediastinal windows for image segmentation has a significant impact on extracting image features. Therefore, choosing lung or mediastinal windows for feature extraction should be carefully considered, as the size of the image segmentation range has a significant impact on image features. The impact of lung squamous cell carcinoma and adenocarcinoma on imaging features is also significant, indicating a high possibility of distinguishing between squamous cell carcinoma and adenocarcinoma based on radiomics (Liu C, He Y, Luo J, The Influence of Image Selection and Segmentation on the Extraction of Lung Cancer Imaging Radiomics Features Using 3D-Slicer Software, 2024).
Authors
- Chunmei Liu (ORCID: https://orcid.org/0000-0002-4109-4387)
- J M Luo (ORCID: https://orcid.org/0009-0005-3963-8575)
- Yuzheng He
Institutions
- Hebei Medical University (CN)
- Second Hospital of Hebei Medical University (CN)
Publication Details
- Journal
- BMC Cancer
- Published
- 2025-04-17
- DOI
- https://doi.org/10.1186/s12885-025-14094-z
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36