Issue |
MATEC Web of Conferences
Volume 61, 2016
The International Seminar on Applied Physics, Optoelectronics and Photonics (APOP 2016)
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Article Number | 02010 | |
Number of page(s) | 6 | |
Section | Chapter 2 Electronic Technology and Electrical Engineering | |
DOI | https://doi.org/10.1051/matecconf/20166102010 | |
Published online | 28 June 2016 |
Segmentation of MRI Volume Data Based on Clustering Method
1 Gansu Radio & TV University, Lanzhou, 730000, China
2 School of information Science & Engineering, Lanzhou University, 730000, Lanzhou, China
3 State Gride Gansu Electric Power Company, Lanzhou, 730000, China.
Here we analyze the difficulties of segmentation without tag line of left ventricle MR images, and propose an algorithm for automatic segmentation of left ventricle (LV) internal and external profiles. Herein, we propose an Incomplete K-means and Category Optimization (IKCO) method. Initially, using Hough transformation to automatically locate initial contour of the LV, the algorithm uses a simple approach to complete data subsampling and initial center determination. Next, according to the clustering rules, the proposed algorithm finishes MR image segmentation. Finally, the algorithm uses a category optimization method to improve segmentation results. Experiments show that the algorithm provides good segmentation results.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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