@inproceedings{404b8e76d4584cb2884baf11bf87e17b,
title = "Weighted local mutual information for 2D-3D registration in vascular interventions",
abstract = "In this paper, a new similarity measure, WLMI (Weighted Local Mutual Information), based on weighted patch and mutual information is proposed to register the preoperative 3D CT model to the intra-operative 2D X-ray images in vascular interventions. We embed this metric into the 2D-3D registration framework, where we show that the robustness and accuracy of the registration can be effectively improved by adapting the strategy of local image patch selection and the weighted joint distribution calculation based on gradient. Experiments on both synthetic and real X-ray image registration show that the proposed method produces considerably better registration results in a shorter time compared with the conventional MI and Normalized MI methods.",
keywords = "2D-3D registration, Gradient weighted, Local patch, Mutual information",
author = "Cai Meng and Qi Wang and Shaoya Guan and Yi Xie",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition, SSPR 2018 and Statistical Techniques in Pattern Recognition, SPR 2018 ; Conference date: 17-08-2018 Through 19-08-2018",
year = "2018",
doi = "10.1007/978-3-319-97785-0\_36",
language = "英语",
isbn = "9783319977843",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "376--385",
editor = "Hancock, \{Edwin R.\} and Ho, \{Tin Kam\} and Battista Biggio and Wilson, \{Richard C.\} and Antonio Robles-Kelly and Xiao Bai",
booktitle = "Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, S+SSPR 2018, Proceedings",
address = "德国",
}