31P-MRS data analysis of liver based on back-propagation neural networks
10.3321/j.issn:1003-3289.2009.10.040
- VernacularTitle:基于反向传输神经网络的肝脏31P磁共振波谱分析
- Author:
Shaoqing WANG
;
Yihui LIU
;
Lijuan WANG
;
Qiang LIU
;
Jinyong CHENG
;
Baopeng LI
- Publication Type:Journal Article
- Keywords:
~(31)P-hosphorus;
Magnetic resonance spectroscopy;
Liver neoplasms;
Neural network
- From:
Chinese Journal of Medical Imaging Technology
2009;25(10):1875-1878
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the value of distinguishment of hepatocellular carcinoma (HCC), cirrhosis nodules and normal liver based on neural networks in the ~(31)P-MR spectroscopy. MethodsA total of 66 data of ~(31)P-MRS were analysed using back-propagation neural network, including 37 samples of liver cirrhosis, 13 samples of HCC and 16 samples of normal liver. ResultsThe cross-valiation experiments showed that diagnostic accuracy rate of HCC increased from 85.47% to 92.31% with neural network model based on the ~(31)P-MR spectroscopy data analysis. Conclusion ~(31) P-MRS data analysis based on neural network model provides a valuable diagnostic tool of HCC in vivo.
