Chen, J.; Yang, J.; Wang, J.; Zhao, Z.; Wang, M.; Sun, C.; Song, N.; Feng, S.
Study on an Automatic Classification Method for Determining the Malignancy Grade of Glioma Pathological Sections Based on Hyperspectral Multi-Scale Spatial–Spectral Fusion Features. Sensors 2024, 24, 3803.
https://doi.org/10.3390/s24123803
AMA Style
Chen J, Yang J, Wang J, Zhao Z, Wang M, Sun C, Song N, Feng S.
Study on an Automatic Classification Method for Determining the Malignancy Grade of Glioma Pathological Sections Based on Hyperspectral Multi-Scale Spatial–Spectral Fusion Features. Sensors. 2024; 24(12):3803.
https://doi.org/10.3390/s24123803
Chicago/Turabian Style
Chen, Jiaqi, Jin Yang, Jinyu Wang, Zitong Zhao, Mingjia Wang, Ci Sun, Nan Song, and Shulong Feng.
2024. "Study on an Automatic Classification Method for Determining the Malignancy Grade of Glioma Pathological Sections Based on Hyperspectral Multi-Scale Spatial–Spectral Fusion Features" Sensors 24, no. 12: 3803.
https://doi.org/10.3390/s24123803
APA Style
Chen, J., Yang, J., Wang, J., Zhao, Z., Wang, M., Sun, C., Song, N., & Feng, S.
(2024). Study on an Automatic Classification Method for Determining the Malignancy Grade of Glioma Pathological Sections Based on Hyperspectral Multi-Scale Spatial–Spectral Fusion Features. Sensors, 24(12), 3803.
https://doi.org/10.3390/s24123803
