A Novel Integration Scheme Based on Mean Shift and Region-Scalable Fitting Level Set for Medical Image Segmentation

DOI

10.2991/icmmita-15.2015.70How to use a DOI?

Keywords

Medical Image Segemntation; Mean Shift; Level Set; Integration Scheme

Abstract

In this study, a novel integration scheme for coupling the results of mean shift with initial contours of the region-scalable fitting level set method (RSF model) is presented. There are two main contributions in the study. First, a new adaptive threshold formula to fit dynamic range of the mean shift clustering results is proposed. Second, a double-side mapping mode is presented to improve the robustness of initialization. Experimental results demonstrate the adaptability and robustness of the proposed method, and accurate segmentation could be obtained for medical images.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - PeiRui Bai
AU  - Dandan Song
AU  - Lijun Bi
AU  - Lei Li
AU  - Tao Qi
PY  - 2015/11
DA  - 2015/11
TI  - A Novel Integration Scheme Based on Mean Shift and Region-Scalable Fitting Level Set for Medical Image Segmentation
BT  - Proceedings of the 2015 3rd International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 357
EP  - 365
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-15.2015.70
DO  - 10.2991/icmmita-15.2015.70
ID  - Bai2015/11
ER  -