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Pulmonary Nodule Registration using Template Matching in Serial CT Scans  

Jo, Hyun-Hee (서울여자대학교 미디어학부)
Hong, He-Len (서울여자대학교 미디어학부)
Publication Information
Journal of KIISE:Software and Applications / v.36, no.8, 2009 , pp. 623-632 More about this Journal
Abstract
In this paper, we propose a pulmonary nodule registration for the tracking of lung nodules in sequential CT scans. Our method consists of following five steps. First, a translational mismatch is corrected by aligning the center of optimal bounding volumes including each segmented lung. Second, coronal maximum intensity projection(MIP) images including a rib structure which has the highest intensity region in baseline and follow-up CT series are generated. Third, rigid transformations are optimized by normalized average density differences between coronal MIP images. Forth, corresponding nodule candidates are defined by Euclidean distance measure after rigid registration. Finally, template matching is performed between the nodule template in baseline CT image and the search volume in follow-up CT image for the nodule matching. To evaluate the result of our method, we performed the visual inspection, accuracy and processing time. The experimental results show that nodules in serial CT scans can be rapidly and correctly registered by coronal MIP-based rigid registration and local template matching.
Keywords
Computed Tomography; Lung Nodule; Coronal Maximum Intensity Projection; Rigid Registration; Template Matching;
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