A Variation Level Set Formulation Local Based C-V Model for Medical Images Segmentation

DOI

10.2991/iccia.2012.130How to use a DOI?

Keywords

GACM, mediccal image segmentation, intensity imhomogeneity, C-V model.

Abstract

Local image information is crucial for accurate segmentation of images with intensity inhomogeneity which usually occurs in medical images. However, image information in local region is not incorporated in popular region-based active contour models, such as piecewise constant models and piecewise smooth models. In this paper, a method which is able to use local information is proposed. The main point is the introduction of the local fitting information expressed by a kernel function which is crucial for segmentation. Our method is based on piecewise constant Chan-Vese model, and compare with different methods for several synthetic images and medical images.

Copyright

© 2013, 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  - Yan Yu
AU  - Chaobing Huang
AU  - Ling Li
PY  - 2014/05
DA  - 2014/05
TI  - A Variation Level Set Formulation Local Based C-V Model for Medical Images Segmentation
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 539
EP  - 542
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.130
DO  - 10.2991/iccia.2012.130
ID  - Yu2014/05
ER  -