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).

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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
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article

Dual-channel grouped cross-dimension attention V-Net for pulmonary nodule segmentation

Wenwu Zhang, Yingbo Liang, Tong Liu, Junding Sun et al.
Quantitative Imaging in Medicine and Surgery
Lung Cancer Diagnosis and Treatment
article

Dual-channel grouped cross-dimension attention V-Net for pulmonary nodule segmentation

Wenwu Zhang, Yingbo Liang, Tong Liu, Junding Sun, Yuzhuo Li, Lihong Zhang
article en

Abstract

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).

Quantitative Imaging in Medicine and SurgeryVol. 15(10)
Henan Polytechnic University (CN)
Openalex Percentile: Top 63%
Lung Cancer Diagnosis and Treatment
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