  Thermal ablation is a minimally invasive procedure for treat-ing small or
unresectable tumors. Although CT is widely used for guiding ablation
procedures, the contrast of tumors against surrounding normal tissues in CT
images is often poor, aggravating the difficulty in accurate thermal ablation.
In this paper, we propose a fast MR-CT image registration method to overlay a
pre-procedural MR (pMR) image onto an intra-procedural CT (iCT) image for
guiding the thermal ablation of liver tumors. By first using a Cycle-GAN model
with mutual information constraint to generate synthesized CT (sCT) image from
the cor-responding pMR, pre-procedural MR-CT image registration is carried out
through traditional mono-modality CT-CT image registration. At the
intra-procedural stage, a partial-convolution-based network is first used to
inpaint the probe and its artifacts in the iCT image. Then, an unsupervised
registration network is used to efficiently align the pre-procedural CT (pCT)
with the inpainted iCT (inpCT) image. The final transformation from pMR to iCT
is obtained by combining the two estimated transformations,i.e., (1) from the
pMR image space to the pCT image space (through sCT) and (2) from the pCT image
space to the iCT image space (through inpCT). Experimental results confirm that
the proposed method achieves high registration accuracy with a very fast
computational speed.
