Automatic liver tumor diagnosis with Dynamic-Contrast Enhanced MRI

Dynamic-Contrast Enhanced MRI (DCE-MRI) is currently used as a complementary diagnosis tool to assess the malignancy of the liver tumor, called hepatoma, hepatocarcinoma, hepatocellular carcinoma or adult primary liver cancer. This paper proposes a set of features and computation methods to extract them in order to design a classifier for automatic diagnosis of the hepatoma. It is shown that the Maximum, WashIn and WashOut rates of the perfusion curves at each voxel obtained from DCE-MRI are adequate discriminative features to automatically classify the tumors with respect to its malignancy. A dynamic discrete linear pharmacokinetic (PK) model is used to estimate the perfusion curves from the noisy observations, based on the multi-compartment paradigm. The arterial response to the contrast agent bolus injection, called arterial input function (AIF), is also estimated since no arteries are available in the neighborhood of the tumor. The compensation of involuntary movements of the pati...

• Type: Conference
• Year: 2008
• Where: ICIP
• Authors: Liliana Caldeira, Isabela Silva, João Sanches
• Keywords: Adequate Discriminative Features, Arterial Input Function, Contrast Agent Bolus, ICIP 2008, Image Processing, Liver Tumor, WashOut Rates