Evaluation of Morphological Reconstruction, Fast Marching and a Novel Hybrid Segmentation Method

3Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

Abstract

An evaluation of two traditional segmentation algorithms of Morphological Reconstruction and the Fast Marching method along with a novel hybrid segmentation approach is presented. After introducing the Fast Marching and the Morphological Reconstruction segmentation, we propose a novel hybrid segmentation approach in multi-stage, which is derived from both an improved Fast Marching method and the Morphological Reconstruction. To demonstrate the effectiveness and accuracy of the three methods, we employ an MRI brain image in our experiments, in which "gold standard" is known. The evaluation is measured accordingly in accuracy and speed when running a 2.0 GHz based windows XP PC. The accuracy results of average 0.9738, 0.6302 and 0.9734 measured in similarity indexes of the Morphological Reconstruction, the Fast Marching and the hybrid approach are achieved, respectively. The computing performance required 188.6, 22.3 and 43.4 in seconds accordingly. © Springer-Verlag 2004.

Cite

CITATION STYLE

APA

Xu, J., & Gu, L. (2004). Evaluation of Morphological Reconstruction, Fast Marching and a Novel Hybrid Segmentation Method. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3314, 678–684. https://doi.org/10.1007/978-3-540-30497-5_106

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free