APA (7th ed.) Citation

Ai, H., Huang, Y., Tai, D., Tsui, P., & Zhou, Z. (2024). Ultrasonic Assessment of Liver Fibrosis Using One-Dimensional Convolutional Neural Networks Based on Frequency Spectra of Radiofrequency Signals with Deep Learning Segmentation of Liver Regions in B-Mode Images: A Feasibility Study. Sensors (14248220), 24(17), 5513. https://doi.org/10.3390/s24175513

Chicago Style (17th ed.) Citation

Ai, Haiming, Yong Huang, Dar-In Tai, Po-Hsiang Tsui, and Zhuhuang Zhou. "Ultrasonic Assessment of Liver Fibrosis Using One-Dimensional Convolutional Neural Networks Based on Frequency Spectra of Radiofrequency Signals with Deep Learning Segmentation of Liver Regions in B-Mode Images: A Feasibility Study." Sensors (14248220) 24, no. 17 (2024): 5513. https://doi.org/10.3390/s24175513.

MLA (9th ed.) Citation

Ai, Haiming, et al. "Ultrasonic Assessment of Liver Fibrosis Using One-Dimensional Convolutional Neural Networks Based on Frequency Spectra of Radiofrequency Signals with Deep Learning Segmentation of Liver Regions in B-Mode Images: A Feasibility Study." Sensors (14248220), vol. 24, no. 17, 2024, p. 5513, https://doi.org/10.3390/s24175513.