摘要
Accurate registration of chest radiographs plays an increasingly important role in medical applications.However, most current intensity-based registration methods rely on the assumption of intensity conservation that is not suitable for alignment of chest radiographs. In this study, we propose a novel algorithm to match chest radiographs, for which the conventional residual complexity(RC) is modified as the similarity measure and the cubic B-spline transformation is adopted for displacement estimation. The modified similarity measure is allowed to incorporate the neighborhood influence into variation of intensity in a justified manner of the weight, while the transformation is implemented with a registration framework of pyramid structure. The results show that the proposed algorithm is more accurate in registration of chest radiographs, compared with some widely used methods such as the sum-of-squared-differences(SSD), correlation coefficient(CC) and mutual information(MI)algorithms, as well as the conventional RC approaches.
Accurate registration of chest radiographs plays an increasingly important role in medical applications.However, most current intensity-based registration methods rely on the assumption of intensity conservation that is not suitable for alignment of chest radiographs. In this study, we propose a novel algorithm to match chest radiographs, for which the conventional residual complexity(RC) is modified as the similarity measure and the cubic B-spline transformation is adopted for displacement estimation. The modified similarity measure is allowed to incorporate the neighborhood influence into variation of intensity in a justified manner of the weight, while the transformation is implemented with a registration framework of pyramid structure. The results show that the proposed algorithm is more accurate in registration of chest radiographs, compared with some widely used methods such as the sum-of-squared-differences(SSD), correlation coefficient(CC) and mutual information(MI)algorithms, as well as the conventional RC approaches.
作者
相志康
李敏
肖亮
练智超
韦志辉
XIANG Zhikang;LI Min;XIAO Liang;LIAN Zhichao;WEI Zhihui
基金
the Fundamental Research Funds for the Central Universities of China(No.30918011104)
the National Natural Science Foundation of China(Nos.61501241 and 61571230)
the Natural Science Foundation of Jiangsu Province(No.BK20150792)
the Foundation of Shandong Provincial Key Laboratory of Digital Medicine and Computer assisted Surgery(No.SDKL-DMCAS-2018-04)
the China Postdoctoral Science Foundation(No.2015M570450)
the Visiting Scholar Foundation of Key Laboratory of Biorheological Science and Technology(Chongqing University)of Ministry of Education(No.CQKLBST-2018-011)