APA (7th ed.) Citation

Saini, M., Larson, N. B., Fatemi, M., & Alizad, A. (2025). Deep learning based motion correction in ultrasound microvessel imaging approach improves thyroid nodule classification. Scientific Reports, 15(1), 1. https://doi.org/10.1038/s41598-025-02728-y

Chicago Style (17th ed.) Citation

Saini, Manali, Nicholas B. Larson, Mostafa Fatemi, and Azra Alizad. "Deep Learning Based Motion Correction in Ultrasound Microvessel Imaging Approach Improves Thyroid Nodule Classification." Scientific Reports 15, no. 1 (2025): 1. https://doi.org/10.1038/s41598-025-02728-y.

MLA (9th ed.) Citation

Saini, Manali, et al. "Deep Learning Based Motion Correction in Ultrasound Microvessel Imaging Approach Improves Thyroid Nodule Classification." Scientific Reports, vol. 15, no. 1, 2025, p. 1, https://doi.org/10.1038/s41598-025-02728-y.