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Non-rigid surface proximity registration of CT images considering the influence of pleural thickenings

Given two CT thorax images from the same patient taken at two different points in time, a detailed follow-up assessment of pleural thickenings and their growth requires a registration of the regarded image regions. While the spatio-temporal matching of thickenings could be achieved by a rigid registration, the direct visual comparison or the combination of thickening segmentations from different points in time require a more precise registration. We present a new method which provides a non-rigid registration of the 3D image data in the region close to the lung surface, where pleural thickenings are located. A B-spline based approach is used to compensate the non-rigid deformations of the lungs. The control-grid for the B-splines is determined using a non-iterative method, which requires matched feature points from the registered image pair. However, current non-rigid registration methods compensate all changes of the lung surface. This is in our case explicitly undesired for changes caused by pleural thickenings. Therefore, our approach takes the thickenings into account by choosing feature points not directly located on the lung surface. The number of feature points is reduced and only strong features are kept for a 3D block matching.