Ablation is a kind of successful treatment for cancer. The technique inserts a special needle into a tumor and produces
heat from Radiofrequency at the needle tip to ablate the tumor. Open configure MR system can take MR images almost
real time and now is applied in liver cancer treatments. During a surgery, surgeons select images in which liver tumors
are seen clearly, and use them to guide the surgery. However, in some cases with severe chirrhosis, the tumors can't be
visualized in the MR images. In such cases, the combination of preoperative CT images will be greatly helpful, if CT
images can be registered to the position of MR images accurately. It is a difficult work since the shape of the liver in the
MR image is different from that of CT images due to the influent of the surgery. In this paper, we use Bspline based
FFD nonrigid image registration to attack the problem. The method includes four steps. Firstly the MRI inhomogeneity
is corrected. Secondly, parametric active contour with the gradient vector flow is used to extract the liver as region of
interest (ROI) because the method is robust and can obtain satisfied results. Thirdly, affine registration is use to match
CT and MR images roughly. Finally, Bspline based FFD nonrigid registration is applied to obtain accuracy registration.
Experiments show the proposed method is robust and accuracy.
In the X-ray coronary digital subtraction angiography, there are serious motion artifacts and noises, and backgrounds
such as ribs, spine, cathers and etc, which are tube structures and like vessels. It's difficult to separate vessels from the
background automatically if they are close each other. In this paper, an automatic extraction of coronary vessels from X-ray
digital subtraction angiography is proposed. We used edge preserving smooth filter to reduce the noises in the images
and keep the vessel edge firstly. Then affine and B-spline based FFD nonrigid registration is applied to the images.
Compared with the segmentation method, the proposed method can remove background greatly and extract the coronary vessel very well.