Automated registration of 3D X-ray angiography images to magnetic resonance images

An automated algorithm for frameless registration of intra-cranial 3D X-ray angiograms (3DXA) to Magnetic Resonance (MR) images is described and evaluated. The registration procedure starts with the manual designation of a pre-defined anatomical point in both modalities. Then, the registration is performed through an iterative process that alternatively estimates the rotation and translation using an original correlation optimization scheme. The evaluation procedure implied comparisons with both manual (11 cases) and stereotactic frame based (9 cases) registration. The results encompass that manual registration is not a viable method of reference for registering such volumes whereas stereotactic frame (or equivalent means) is acceptable for validation purpose. A maximum error of 4 mm was measured for our automated algorithm while variations of up to 5 mm were considered on the initial point location. Convergence time was below 1 minute while an average time of 30 minutes was required to perform manual registration. This validation procedure demonstrates a good precision for the automated algorithm when compared to a stereotactic frame based matching. Such an algorithm could make the intra-cranial pathology assessment more reliable, enable frameless radiotherapy planning of AVMs in 3D, ease biopsy planning in neurosurgery or be helpful for educational purpose.