Affiliation:
1. Shandong Medical Imaging Research Institute
2. Taishan Medical College
3. Shandong Institute of Light Industry
Abstract
31P MRS(31Phosphorus Magnetic Resonance Spectroscopy) is a non invasive protocol
for analyzing the energetic metabolism and biomedical changes in cellular level. Evaluation of 31P
MRS is important in diagnosis and treatment of many hepatic diseases. In this paper, we apply
back-propagation neural network (BP) and self-organizing map (SOM) neural network to analyze
31P MRS data to distinguish three diagnostic classes of cancer, normal and cirrhosis tissue. 66
samples of 31P MRS data are selected including cancer, normal and cirrhosis tissue. Four
experiments are carried out. Good performance is achieved with limited samples. Experimental
results prove that neural network models based on 31P MRS data offer an alternative and promising
technique for diagnostic prediction of liver cancer in vivo.
Publisher
Trans Tech Publications, Ltd.