Magnetic resonance imaging (MRI) of the liver has demonstrated to be
quite sensitive in showing Hepatic Hemangioma as high intensity lesions
in T2 weighted imaging sequence. Hepatic Hemangioma is a non-malignant
tumor and has relative high occurrence rate among the general
population. It is of importance to differentiate this benign abnormality
from other high intensity malignant lesions, such as
... [Show full abstract] hepatoma,
adenocarcinoma, or metastasis. The objective of our study was to
investigate the feasibility of applying neural network to assist in the
differentiation of the liver MRI lesions. Thirty-seven liver MRI studies
were collected, this including twenty-three cases of hepatic hemangioma
and fourteen cases of malignant tumors. all cases were clinically proven
with the diagnosed pathological condition and verified by biopsy. Four
quantitative features, adopted from published literatures and used
clinically on a routine basis, were measured from MRI images. In this
study, a multilayer and two layer backpropagation networks were used for
performance comparison. By attempting various training methods, the
accuracy of the two layer network had been improved from 74% to 83% by
selecting the proper boundary set based on the euclidean distance for
each data set in both classes when training the network.
