Registration of Chest Radiographs Using A Diffeomorphic Demons Based Method

Chest radiographs are widely used in clinic, typically in diagnosis and treatment of lung tumors. Accurate registration of chest radiographs is surprisingly important by providing correspondence between different images, which is however still a challenge at present. To solve this problem, we propose a diffeomorphic demons based algorithm for registration of chest radiographs in this paper. Specifically, an improved similarity metric is designed in terms of a log Euclidean formulation and solved by a diffeomorphic framework with composition of two stationary velocity fields, which averts heavy computation that often occurs in spatial transformation of the traditional log demons method. To evaluate the performance of the proposed algorithm, qualitative and quantitative validation methods are carried out and subtraction images are generated. Results show that the proposed diffeomorphic demons based algorithm obtain more accurate registration of chest radiographs compared with active demons, additive demons, and traditional log demons methods.