  Krylov subspace methods are considered a standard tool to solve large systems
of linear algebraic equations in many scientific disciplines such as image
restoration or solving partial differential equations in mechanics of
continuum. In the context of computer tomography however, the mostly used
algebraic reconstruction techniques are based on classical iterative schemes.
In this work we present software package that implements fully 3D cone beam
projection operator and uses Krylov subspace methods, namely CGLS and LSQR to
solve related tomographic reconstruction problems. It also implements basic
preconditioning strategies. On the example of the cone beam CT reconstruction
of 3D Shepp-Logan phantom we show that the speed of convergence of the CGLS
clearly outperforms PSIRT algorithm. Therefore Krylov subspace methods present
an interesting option for the reconstruction of large 3D cone beam CT problems.
