Arbitrary cross-sections from biological data based on shape of organs

Techniques for generating a series of cross-sectional images, such as computed tomography (CT), magnetic resonance imaging (MRI) or direct sectioning, enable observation inside living organisms such as human or animal bodies, greatly contributing to medical and biological sciences. However, these techniques can interpret the cross-sections only in a prescribed direction and at certain large intervals limited by hardware. Furthermore, they do not allow immediate observation of arbitrary cross-sections. Straightforward linear interpolation can lead to artifacts in regions with large intensity gradients, particularly near the organ boundaries. This paper's main purpose is to solve the problem of image interpolation for generating with high precision an arbitrary cross-section from a series of slices. This procedure is carried out by incorporating reconstructed organ shapes. The results are presented as biological data.