1. Abstract  Dynamic Contrast Enhanced Magnetic Resonance Images has proven to be the most efficient diagnose method for liver tumor identification.  DCE-MRI capabilities can be considerably increased applying pharmokinetic analysis.  The liver has dual-blood supply, receiving 25% from the hepatic artery and 75 % from the hepatic portal vein. However, this balanced can be altered locally or globally in several pathological conditions, like in liver cancer.  The method proposed allows assessing differences between benign and malign liver tumors, namely in terms of its arterial ratio. Liver Tumor Classification based on DCE-MRI Images RecPad2010 - 16th edition of the Portuguese Conference on Pattern Recognition, UTAD University, Vila Real city, October 29th Nuno P. Barros and J.Miguel Sanches Institute for Systems and Robotics / Instituto Superior Técnico Lisboa, Portugal Experimental Results  Here we present two maps of the arterial ratio in two different livers with Hepatocellular Carcinoma (HCC). Three tumors are visible. The γ maps are compared with the corresponding arterial phase MR images.  Now results from a benign lesion (Focal Nodular Hyperplasia) and a malignant one (HCC) are shown. The parameter maps are accompanied by the corresponding dynamic contrast multiphasic MR images. The results shown demonstrate that the model used was able to detect some of the known differences between benign and malign liver lesions, namely in terms of the arterial ratio, wash-out rate and perfusion volume. Bibliography [1] - M. Orton, K. Miyazaki, D. Koh, D. Collins, D. Hawkes, D. Atkinson, and M. Leach. Optimizing functional parameter accuracy for breath-hold DCE-MRI of liver tumours. Physics in medicine and biology, 54:2197, 2009. [2] - P. Tofts, G. Brix, D. Buckley, J. Evelhoch, E. Henderson, M. Knopp, H. Larsson, T. Lee, N. Mayr, G. Parker, et al. Estimating kinetic parameters from dynamic contrast-enhanced T1-weighted MRI of a difusable tracer: standardized quantities and symbols. Journal of Magnetic Resonance Imaging,10(3):223{232, 1999. Problem Formulation  Considering a linear relation between contrast concentration and image intensity, one can approximate the amount of contrast in one voxel by: where I(t,x,y,z) is the image intensity at time t in the voxel with coordinates (x,y,z).  The contrast concentration observed in one liver voxel can be modeled considering the signal retrieved from the aorta and the hepatic portal vein: where C L is the liver contrast concentration measured in one voxel, K L trans and k L are two constants to determine, and C i is the input contrast concentration, given by: where C A is the contrast concentration in the aorta, C V is the contrast concentration in the hepatic portal vein and γ is the arterial ratio.  The model used can be described by the following diagram: Here AIF and PIF represent the Arterial and Portal input Functions.  The model is applied in each liver voxel and a group of parameters is retrieved and analyzed.