Department of Multimedia Engineering, College of Information and Media, Seoul Women's University, 126 Gongreung-dong, Nowon-gu, Seoul 139-774, Republic of Korea.
Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul 110-744, Republic of Korea.
Comput Biol Med. 2014 Feb;45:87-97. doi: 10.1016/j.compbiomed.2013.10.028. Epub 2013 Nov 5.
We propose an automatic nodule registration method between baseline and follow-up chest CT scans. Initial alignment using the center of the lung volume corrects the gross translational mismatch, and rigid registration using coronal and sagittal maximum intensity projection images effectively refines the rigid motion of the lungs. Nodule correspondences are established by finding the most similar region in terms of density as well as the geometrical constraint. The proposed nodule registration method increased the nodule hit rate (the ratio of the number of successfully matched nodules to total nodule number) from 26% to 100%.
我们提出了一种基于基线和随访胸部 CT 扫描的自动结节配准方法。使用肺容积中心进行初始配准可纠正大体平移失配,使用冠状面和矢状面最大密度投影图像进行刚性配准可有效细化肺部的刚性运动。通过寻找密度最相似的区域以及几何约束来建立结节对应关系。所提出的结节配准方法将结节命中率(成功匹配的结节数与总结节数的比值)从 26%提高到 100%。