计算机工程与应用2019，Vol.55Issue(3)：202-208,7.DOI:10.3778/j.issn.1002-8331.1711-0288
基于自适应薄板样条全变分的肺CT/PET图像配准
CT/PET Lung Registration Using Adaptive Thin Plate Spline-Based Total Variation Regularization
摘要
Abstract
The discontinuities displacement field at the boundaries is preserved through Total Variation(TV)regularization when registering organ images with sliding motion. But TV assumes a global regularization which will lead poor corre-spondences at local areas of images. This paper creates adaptive Thin Plate Spline-based Total Variation(TPS-TV)regu-larization combining Thin Plate Spline(TPS)and TV operator according to the distance of pixels to boundaries. Then this paper chooses Correlation Ratio-based Mutual Information(CRMI)similarity measure function and Limited-memory Broyden Fletcher Goldfarb Shanno(L-BFGS)optimization to establish a non-rigid registration frame. Compared with TV and TPS regularization on the public DIR-Lab dataset and clinical CT/PET dataset, the proposed method has been demon-strated a more dependable displacement field and higher registration accuracy.关键词
自适应薄板样条全变分/滑移运动/非刚性配准/肺Key words
adaptive Thin Plate Spline-based Total Variation(TPS-TV)/sliding motion/non-rigid registration/lung分类
信息技术与安全科学引用本文复制引用
杜雪莹,龚伦,刘兆邦,章程,刘含秋,丁敏,郑健..基于自适应薄板样条全变分的肺CT/PET图像配准[J].计算机工程与应用,2019,55(3):202-208,7.基金项目
广东理工学院质量工程项目(No.JPKC2018006). （No.JPKC2018006）
