A sequential geometry-reconstruction-based deep learning approach to improve accuracy and consistence of lumbar spine MRI image segmentation
Published in Proc. SPIE 12926, Medical Imaging 2024, 2024
Recommended citation: Qian, L., Chen, J., Ma, L., Urakov, T., & Liang, L. (2024). "A sequential geometry-reconstruction-based deep learning approach to improve accuracy and consistence of lumbar spine MRI image segmentation." Proc. SPIE 12926, Medical Imaging 2024. https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12926/1292634/A-sequential-geometry-reconstruction-based-deep-learning-approach-to-improve/10.1117/12.3007064.short
Recommended citation: Qian, L., Chen, J., Ma, L., Urakov, T., & Liang, L. (2024). “A sequential geometry-reconstruction-based deep learning approach to improve accuracy and consistence of lumbar spine MRI image segmentation.” Proc. SPIE 12926, Medical Imaging 2024.
