Dual-channel grouped cross-dimension attention V-Net for pulmonary nodule segmentation
Based on experimental data, the strategy presented in this study significantly improves lung nodule segmentation accuracy. The ablation tests also confirm the proposed module's strong segmentation and generalization abilities. This segmentation model is expected to be applied to other medical segmentations. Our solution is open-source and online (https://github.com/freshmancodes/Pulmonary-Nodule-Segmentation).
Authors
- Wenwu Zhang (ORCID: https://orcid.org/0000-0002-1402-3508)
- Yingbo Liang
- Tong Liu (ORCID: https://orcid.org/0000-0002-0284-486X)
- Junding Sun (ORCID: https://orcid.org/0000-0001-7349-0248)
- Yuzhuo Li
- Lihong Zhang (ORCID: https://orcid.org/0000-0003-4981-2555)
Institutions
- Henan Polytechnic University (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-09-24
- DOI
- https://doi.org/10.21037/qims-24-2434
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00