Reconstruction of Tomographic Data by Markov Random Fields
Marek Zimanyi Department of Computer Graphics and Image Processing Comenius University Bratislava, Slovakia |

Traditional reconstruction techniques are based on
the convolution of interpolation filter with sampled data. The problem
arises when the slices are scanned with big distances. This problem is
formulated by *Shanon* ([WEIT], [PM]):
Sampling interval *T* has to fulfill the relation *T *<
(1/2*f _{max}*), where 2

Sampling a signal at a rate lower than postulated by Shannon leads to a very serious parasitic effect:

In our case (CT slices) aliasing appears because each slice is scanned with some radiation dose and high resolution CT data are usually taken only from cadavers. In MRI tomography, scanning a sufficient number of slices for 3D reconstruction requires medically unacceptable time.