This paper presents a method for biventricular myocardial deformation recovery from cine MRI. The method is based on a deformable model that is nearly incompressible, a desirable property since the myocardium has been shown to be nearly incompressible. The model uses a matrix-valued radial basis function to represent divergence-free displacement fields, which is a first order approximation of incompressibility. This representation allows for deformation modeling of an arbitrary topologies with a relatively small number of parameters, which is suitable for representing the motion of the multi-chamber structure of the heart. The myocardium needs to be segmented in an initial frame after which the method automatically determines the tissue deformation everywhere in the myocardium throughout the cardiac cycle. Two studies were carried out to validate the method. In the first study the myocardial deformation was recovered from a 3D anatomical cine MRI sequence of a healthy volunteer and then validated against the manual segmentation of the biventricular wall and against the corresponding 3D tagged cine MRI sequence. The average volume agreement between the model and the manual segmentation had a false positive rate of 3.2%, false negative rate of 2.8% and true positive rate of 91.4%. The average distance between the model and manually determined intersections of perpendicular tag planes was 1.7mm (1.2 pixel). The same procedures was repeated on another set of 3D anatomical and tagged MRI scans of the same volunteer taken four months later. The recovered deformation was very similar to the one obtained from the first set of scans. In the second study the method was applied to 3D anatomical cine MRI scans of three patients with ventricular dyssynchrony and three age-matched healthy volunteers. The recovered strains of the normal subjects were clearly stronger than the recovered strains of the patients and they were similar to those reported by other researchers. The recovered deformation of all six subjects was validated against manual segmentation of the biventricular wall and against corresponding tagged MRI scans. The agreement was similar to that of the first study.