APA (7th ed.) Citation

Yang, H., Zhang, Z., Tian, L., Dang, P., Wan, L., Zhou, Z., . . . Chen, J. (2026). Deep learning–based CT slice synthesis improves radiomic feature reproducibility and discriminative performance in lung nodule assessment. Insights into Imaging, 17(1), 1. https://doi.org/10.1186/s13244-026-02338-w

Chicago Style (17th ed.) Citation

Yang, Hujun, et al. "Deep Learning–based CT Slice Synthesis Improves Radiomic Feature Reproducibility and Discriminative Performance in Lung Nodule Assessment." Insights into Imaging 17, no. 1 (2026): 1. https://doi.org/10.1186/s13244-026-02338-w.

MLA (9th ed.) Citation

Yang, Hujun, et al. "Deep Learning–based CT Slice Synthesis Improves Radiomic Feature Reproducibility and Discriminative Performance in Lung Nodule Assessment." Insights into Imaging, vol. 17, no. 1, 2026, p. 1, https://doi.org/10.1186/s13244-026-02338-w.