Steger, Sebastian ; Wesarg, Stefan (2012)
Automated Skeleton Based Multi-modal Deformable Registration of Head&Neck Datasets.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012: Part II.
doi: 10.1007/978-3-642-33418-4_9
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
This paper presents a novel skeleton based method for the registration of head&neck datasets. Unlike existing approaches it is fully automated, spatial relation of the bones is considered during their registration and only one of the images must be a CT scan. An articulated atlas is used to jointly obtain a segmentation of the skull, the mandible and the vertebrae C1-Th2 from the CT image. These bones are then successively rigidly registered with the moving image, beginning at the skull, resulting in a rigid transformation for each of the bones. Linear combinations of those transformations describe the deformation in the soft tissue. The weights for the transformations are given by the solution of the Laplace equation. Optionally, the skin surface can be incorporated. The approach is evaluated on 20 CT/MRI pairs of head&neck datasets acquired in clinical routine. Visual inspection shows that the segmentation of the bones was successful in all cases and their successive alignment was successful in 19 cases. Based on manual segmentations of lymph nodes in both modalities, the registration accuracy in the soft tissue was assessed. The mean target registration error of the lymph node centroids was 5.33 ± 2.44 mm when the registration was solely based on the deformation of the skeleton and 5.00 ± 2.38 mm when the skin surface was additionally considered. The method's capture range is sufficient to cope with strongly deformed images and it can be modified to support other parts of the body. The overall registration process typically takes less than 2 minutes.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2012 |
| Autor(en): | Steger, Sebastian ; Wesarg, Stefan |
| Art des Eintrags: | Bibliographie |
| Titel: | Automated Skeleton Based Multi-modal Deformable Registration of Head&Neck Datasets |
| Sprache: | Englisch |
| Publikationsjahr: | 2012 |
| Verlag: | Springer, Berlin; Heidelberg; New York |
| Reihe: | Lecture Notes in Computer Science (LNCS); 7511 |
| Veranstaltungstitel: | Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012: Part II |
| DOI: | 10.1007/978-3-642-33418-4_9 |
| Kurzbeschreibung (Abstract): | This paper presents a novel skeleton based method for the registration of head&neck datasets. Unlike existing approaches it is fully automated, spatial relation of the bones is considered during their registration and only one of the images must be a CT scan. An articulated atlas is used to jointly obtain a segmentation of the skull, the mandible and the vertebrae C1-Th2 from the CT image. These bones are then successively rigidly registered with the moving image, beginning at the skull, resulting in a rigid transformation for each of the bones. Linear combinations of those transformations describe the deformation in the soft tissue. The weights for the transformations are given by the solution of the Laplace equation. Optionally, the skin surface can be incorporated. The approach is evaluated on 20 CT/MRI pairs of head&neck datasets acquired in clinical routine. Visual inspection shows that the segmentation of the bones was successful in all cases and their successive alignment was successful in 19 cases. Based on manual segmentations of lymph nodes in both modalities, the registration accuracy in the soft tissue was assessed. The mean target registration error of the lymph node centroids was 5.33 ± 2.44 mm when the registration was solely based on the deformation of the skeleton and 5.00 ± 2.38 mm when the skin surface was additionally considered. The method's capture range is sufficient to cope with strongly deformed images and it can be modified to support other parts of the body. The overall registration process typically takes less than 2 minutes. |
| Freie Schlagworte: | Business Field: Digital society, Research Area: Confluence of graphics and vision, Image registration, Multimodality, Multi-rigid registration, Articulated atlas |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 12 Nov 2018 11:16 |
| Letzte Änderung: | 12 Nov 2018 11:16 |
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