A hybrid optimization model based on multi-metrics for registration using free-form deformation.
We propose a new optimization model for non-rigid registration of images using multi-metrics. The ordinary searching step of optimization has been often trapped in local minima and produces wrong registration results. In this paper, if the condition occurs, multi-metrics model will switch to the other metrics to get rid of the local minima, vice versa. We have tested our approach in a variety of experimental conditions and compared the results with the optimization without multi-metrics. The results indicate that the new model is robust and fast in non-rigid registration.
Song
Jiasi
J
Laboratory of Image Guided Surgery and Therapy, (IGST), Shanghai Jiao Tong University (SJTU), China.
Gu
Lixu
L
Huang
Pengfei
P
Li
Wei
W
Xu
Jianrong
J
D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D014057:Tomography, X-Ray Computed