An Image Registration Method with Radial Feature Points Sampling: Application to Follow-Up CT Scans of a Solitary Pulmonary Nodule

In order to support radiologists' follow-up task of two CT scans captured in the past and in the present, we aimed to develop a system that displays both a region of interest ROI in one image selected by a radiologist and a corresponding ROI in another image. In this paper, we propose a registration method for the system. A typical registration method identifies several pairs of matched feature points i.e., matching pairs between two images within the range of a predefined distance from the ROI's center point i.e., interest point to correct a positional shift of an organ caused by heartbeats and breathing. However, low accuracy of registration is often observed because of biased distribution or a small number of matching pairs, depending on the sampling range. We developed a novel registration method that radially and evenly searches for several nearest matching pairs around the interest point and then estimates a translation vector at the interest point as a weighted average of these nearest pairs using a weighting factor based on its distance from the interest point. This method was based on the assumption that the transformation of an interest point work with the transformation of a near point since the lung is a continuum. The results of a comparative evaluation of the existing method and the proposed method on the basis of 15 cases showed that the accuracy of the proposed method was higher than that of the existing method in 13/15 cases. We analyzed the association between the accuracy and the range of sampling and found that the accuracy of the proposed method was similar to the best performance of the existing method with an ideal range of sampling the matching pairs. Finally, we showed evidence that the new method was reasonably consistent in terms of giving the best performance.