@inproceedings{17fd46d284634dd2828e4bafe181ecd2,
title = "Landmark correspondence optimization for coupled surfaces",
abstract = "Volumetric layers are often encountered in medical images. Unlike solid structures, volumetric layers are characterized by double and nested bounding surfaces. It is expected that better statistical models can be built by utilizing the surface coupleness rather than simply applying the landmarking method on each of them separately. We propose an approach to optimizing the landmark correspondence on the coupled surfaces by minimizing the description length that incorporates local thickness gradient. The evaluations are performed on a set of 2-D synthetic close coupled contours and a set of real-world open surfaces, the skull vaults. Compared with performing landmarking separately on the coupled surfaces, the proposed method constructs models that have better generalization ability and specificity.",
author = "Lin Shi and Defeng Wang and Heng, \{Pheng Ann\} and Wong, \{Tien Tsin\} and Chu, \{Winnie C.W.\} and Yeung, \{Benson H.Y.\} and Cheng, \{Jack C.Y.\}",
year = "2007",
doi = "10.1007/978-3-540-75759-7\_99",
language = "英语",
isbn = "9783540757580",
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 = "818--825",
booktitle = "Medical Image Computing and Computer-Assisted Intervention - MICCAI 2007 - 10th International Conference, Proceedings",
address = "德国",
edition = "PART 2",
note = "10th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2007 ; Conference date: 29-10-2007 Through 02-11-2007",
}