Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 725-734 |
| Seitenumfang | 10 |
| Fachzeitschrift | Computerized Medical Imaging and Graphics |
| Jahrgang | 38 |
| Ausgabenummer | 8 |
| Publikationsstatus | Veröffentlicht - 23 Juni 2014 |
Abstract
Medical image segmentation and anatomical structure labeling according to the types of the tissues are important for accurate diagnosis and therapy. In this paper, we propose a novel approach for multi-region labeling and segmentation, which is based on a topological graph prior and the topological information of an atlas, using a modified multi-level set energy minimization method in brain images. We consider a topological graph prior and atlas information to evolve the contour based on a topological relationship presented via a graph relation. This novel method is capable of segmenting adjacent objects with very close gray level in low resolution brain image that would be difficult to segment correctly using standard methods. The topological information of an atlas are transformed to the topological graph of a low resolution (noisy) brain image to obtain region labeling. We explain our algorithm and show the topological graph prior and label transformation techniques to explain how it gives precise multi-region segmentation and labeling. The proposed algorithm is capable of segmenting and labeling different regions in noisy or low resolution MRI brain images of different modalities. We compare our approaches with other state-of-the-art approaches for multi-region labeling and segmentation.
ASJC Scopus Sachgebiete
- Gesundheitsberufe (insg.)
- Radiologie- und Ultraschalltechnik
- Medizin (insg.)
- Radiologie, Nuklearmedizin und Bildgebung
- Informatik (insg.)
- Maschinelles Sehen und Mustererkennung
- Medizin (insg.)
- Gesundheitsinformatik
- Informatik (insg.)
- Computergrafik und computergestütztes Design
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in: Computerized Medical Imaging and Graphics, Jahrgang 38, Nr. 8, 23.06.2014, S. 725-734.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Multi-region labeling and segmentation using a graph topology prior and atlas information in brain images
AU - Al-Shaikhli, Saif Dawood Salman
AU - Yang, Michael Ying
AU - Rosenhahn, Bodo
N1 - Funding information: The work was partially funded by DAAD scholarship (A/10/96106) and MOHESR-Iraq (Baghdad University). The authors gratefully acknowledge these supports.
PY - 2014/6/23
Y1 - 2014/6/23
N2 - Medical image segmentation and anatomical structure labeling according to the types of the tissues are important for accurate diagnosis and therapy. In this paper, we propose a novel approach for multi-region labeling and segmentation, which is based on a topological graph prior and the topological information of an atlas, using a modified multi-level set energy minimization method in brain images. We consider a topological graph prior and atlas information to evolve the contour based on a topological relationship presented via a graph relation. This novel method is capable of segmenting adjacent objects with very close gray level in low resolution brain image that would be difficult to segment correctly using standard methods. The topological information of an atlas are transformed to the topological graph of a low resolution (noisy) brain image to obtain region labeling. We explain our algorithm and show the topological graph prior and label transformation techniques to explain how it gives precise multi-region segmentation and labeling. The proposed algorithm is capable of segmenting and labeling different regions in noisy or low resolution MRI brain images of different modalities. We compare our approaches with other state-of-the-art approaches for multi-region labeling and segmentation.
AB - Medical image segmentation and anatomical structure labeling according to the types of the tissues are important for accurate diagnosis and therapy. In this paper, we propose a novel approach for multi-region labeling and segmentation, which is based on a topological graph prior and the topological information of an atlas, using a modified multi-level set energy minimization method in brain images. We consider a topological graph prior and atlas information to evolve the contour based on a topological relationship presented via a graph relation. This novel method is capable of segmenting adjacent objects with very close gray level in low resolution brain image that would be difficult to segment correctly using standard methods. The topological information of an atlas are transformed to the topological graph of a low resolution (noisy) brain image to obtain region labeling. We explain our algorithm and show the topological graph prior and label transformation techniques to explain how it gives precise multi-region segmentation and labeling. The proposed algorithm is capable of segmenting and labeling different regions in noisy or low resolution MRI brain images of different modalities. We compare our approaches with other state-of-the-art approaches for multi-region labeling and segmentation.
KW - Atlas information
KW - Labeling
KW - Medical image
KW - Multi-level set
KW - Multi-region
KW - Segmentation
KW - Topological graph
UR - http://www.scopus.com/inward/record.url?scp=84911991809&partnerID=8YFLogxK
U2 - 10.1016/j.compmedimag.2014.06.008
DO - 10.1016/j.compmedimag.2014.06.008
M3 - Article
C2 - 24998760
AN - SCOPUS:84911991809
VL - 38
SP - 725
EP - 734
JO - Computerized Medical Imaging and Graphics
JF - Computerized Medical Imaging and Graphics
SN - 0895-6111
IS - 8
ER -