@inproceedings{8d23c5dc60684930b73aeeeaf3d0b512,
title = "Greedy algorithm based deformable simplex meshes using gradient vector flow as external energy",
abstract = "Deformable models have been quite popular in medical image analysis, particularly in image segmentation. However, when applied to 3D volumetric data, their high computational cost can be a problem. In this paper, we describe a new efficient 3D segmentation method based on deformable simplex meshes. The greedy algorithm, which has proven more computational efficient and robust than physics-based method, is employed to perform the shape deformation. Generalized gradient vector flow (GGVF) field is a classical external force for physics-based deformable models. We adapt it for greedy algorithm as external energy to overcome the main issues of the traditional external energy (i.e., sensitivity to shape initialization and poor convergence to the long and thin boundary concavities). Results of applying our method to both synthetic and clinical images are presented to illustrate the accuracy and robustness of our proposed method.",
keywords = "Deformable models, GGVF energy, Greedy algorithm, Simplex meshes",
author = "Changfa Shi and Changyong Guo and Yuanzhi Cheng and Jinke Wang",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 7th International Conference on BioMedical Engineering and Informatics, BMEI 2014 ; Conference date: 14-10-2014 Through 16-10-2014",
year = "2014",
doi = "10.1109/BMEI.2014.7002770",
language = "英语",
series = "Proceedings - 2014 7th International Conference on BioMedical Engineering and Informatics, BMEI 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "199--204",
booktitle = "Proceedings - 2014 7th International Conference on BioMedical Engineering and Informatics, BMEI 2014",
address = "美国",
}