@inproceedings{d948982260eb4f44af37970f5b556cd5,
title = "Registration of 3D FMT and CT images of mouse via affine transformation with Bayesian iterative closest points",
abstract = "It is difficult to directly co-register the 3D FMT (Fluorescence Molecular Tomography) image of a small tumor in a mouse whose maximal diameter is only a few mm with a larger CT image of the entire animal that spans about ten cm. This paper proposes a new method to register 2D flat and projected CT image first to facilitate the registration between small 3D FMT images and large CT images. And a novel algorithm Bayesian Iterative Closest Point (BICP) is introduced and validated in 2D affine registration. The visualization of the alignment of the 3D FMT and CT image through 2D registration shows promising results that would lead to automated 3D registration.",
author = "Xia Zheng and Xiaobo Zhou and Youxian Sun and Wong, {Stephen T C}",
year = "2007",
doi = "10.1007/978-3-540-72393-6_135",
language = "English (US)",
isbn = "9783540723929",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag",
number = "PART 2",
pages = "1140--1149",
booktitle = "Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings",
edition = "PART 2",
note = "4th International Symposium on Neural Networks, ISNN 2007 ; Conference date: 03-06-2007 Through 07-06-2007",
}