The Accuracy and Radiomics Feature Effects of Multiple U-net-Based Automatic Segmentation Models for Transvaginal Ultrasound Images of Cervical Cancer.

MLA

Jin, Juebin, et al. “The Accuracy and Radiomics Feature Effects of Multiple U-Net-Based Automatic Segmentation Models for Transvaginal Ultrasound Images of Cervical Cancer.” Journal of Digital Imaging, vol. 35, no. 4, Aug. 2022, pp. 983–92. EBSCOhost, https://doi.org/10.1007/s10278-022-00620-z.

APA

Jin, J., Zhu, H., Teng, Y., Ai, Y., Xie, C., & Jin, X. (2022). The Accuracy and Radiomics Feature Effects of Multiple U-net-Based Automatic Segmentation Models for Transvaginal Ultrasound Images of Cervical Cancer. Journal of Digital Imaging, 35(4), 983–992. https://doi.org/10.1007/s10278-022-00620-z

Chicago

Jin, Juebin, Haiyan Zhu, Yingyan Teng, Yao Ai, Congying Xie, and Xiance Jin. 2022. “The Accuracy and Radiomics Feature Effects of Multiple U-Net-Based Automatic Segmentation Models for Transvaginal Ultrasound Images of Cervical Cancer.” Journal of Digital Imaging 35 (4): 983–92. doi:10.1007/s10278-022-00620-z.