Suppr超能文献

使用全局肋骨匹配和结节模板匹配进行连续 CT 扫描中的肺结节注册。

Pulmonary nodule registration in serial CT scans using global rib matching and nodule template matching.

机构信息

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.

出版信息

Comput Biol Med. 2014 Feb;45:87-97. doi: 10.1016/j.compbiomed.2013.10.028. Epub 2013 Nov 5.

Abstract

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%.

摘要

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%。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验