Active Contour Model Coupling with Higher Order Diffusion for Medical Image Segmentation
Active contour models are very popular in image segmentation. Different features such as mean gray and variance are selected for different purpose. But for image with intensity inhomogeneities, there are no features for segmentation using the active contour model. The images with intensity inhomoge...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
|
| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2014/237648 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832567288175263744 |
|---|---|
| author | Guodong Wang Jie Xu Qian Dong Zhenkuan Pan |
| author_facet | Guodong Wang Jie Xu Qian Dong Zhenkuan Pan |
| author_sort | Guodong Wang |
| collection | DOAJ |
| description | Active contour models are very popular in image segmentation. Different features such as mean gray and variance are selected for different purpose. But for image with intensity inhomogeneities, there are no features for segmentation using the active contour model. The images with intensity inhomogeneities often occurred in real world especially in medical images. To deal with the difficulties raised in image segmentation with intensity inhomogeneities, a new active contour model with higher-order diffusion method is proposed. With the addition of gradient and Laplace information, the active contour model can converge to the edge of the image even with the intensity inhomogeneities. Because of the introduction of Laplace information, the difference scheme becomes more difficult. To enhance the efficiency of the segmentation, the fast Split Bregman algorithm is designed for the segmentation implementation. The performance of our method is demonstrated through numerical experiments of some medical image segmentations with intensity inhomogeneities. |
| format | Article |
| id | doaj-art-1516f485f5f848cf9b0bf81bced7bad4 |
| institution | Kabale University |
| issn | 1687-4188 1687-4196 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Biomedical Imaging |
| spelling | doaj-art-1516f485f5f848cf9b0bf81bced7bad42025-02-03T01:01:52ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962014-01-01201410.1155/2014/237648237648Active Contour Model Coupling with Higher Order Diffusion for Medical Image SegmentationGuodong Wang0Jie Xu1Qian Dong2Zhenkuan Pan3College of Information Engineering, Qingdao University, Qingdao 266071, ChinaCollege of Physics Science, Qingdao University, Qingdao 266071, ChinaThe Affiliated Hospital of Medical College, Qingdao University, Qingdao 266003, ChinaCollege of Information Engineering, Qingdao University, Qingdao 266071, ChinaActive contour models are very popular in image segmentation. Different features such as mean gray and variance are selected for different purpose. But for image with intensity inhomogeneities, there are no features for segmentation using the active contour model. The images with intensity inhomogeneities often occurred in real world especially in medical images. To deal with the difficulties raised in image segmentation with intensity inhomogeneities, a new active contour model with higher-order diffusion method is proposed. With the addition of gradient and Laplace information, the active contour model can converge to the edge of the image even with the intensity inhomogeneities. Because of the introduction of Laplace information, the difference scheme becomes more difficult. To enhance the efficiency of the segmentation, the fast Split Bregman algorithm is designed for the segmentation implementation. The performance of our method is demonstrated through numerical experiments of some medical image segmentations with intensity inhomogeneities.http://dx.doi.org/10.1155/2014/237648 |
| spellingShingle | Guodong Wang Jie Xu Qian Dong Zhenkuan Pan Active Contour Model Coupling with Higher Order Diffusion for Medical Image Segmentation International Journal of Biomedical Imaging |
| title | Active Contour Model Coupling with Higher Order Diffusion for Medical Image Segmentation |
| title_full | Active Contour Model Coupling with Higher Order Diffusion for Medical Image Segmentation |
| title_fullStr | Active Contour Model Coupling with Higher Order Diffusion for Medical Image Segmentation |
| title_full_unstemmed | Active Contour Model Coupling with Higher Order Diffusion for Medical Image Segmentation |
| title_short | Active Contour Model Coupling with Higher Order Diffusion for Medical Image Segmentation |
| title_sort | active contour model coupling with higher order diffusion for medical image segmentation |
| url | http://dx.doi.org/10.1155/2014/237648 |
| work_keys_str_mv | AT guodongwang activecontourmodelcouplingwithhigherorderdiffusionformedicalimagesegmentation AT jiexu activecontourmodelcouplingwithhigherorderdiffusionformedicalimagesegmentation AT qiandong activecontourmodelcouplingwithhigherorderdiffusionformedicalimagesegmentation AT zhenkuanpan activecontourmodelcouplingwithhigherorderdiffusionformedicalimagesegmentation |