Becker, Meike ; Kirschner, Matthias ; Fuhrmann, Simon ; Wesarg, Stefan (2011)
Automatic Construction of Statistical Shape Models for Vertebrae.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011: Part II.
doi: 10.1007/978-3-642-23629-7_61
Conference or Workshop Item, Bibliographie
Abstract
For segmenting complex structures like vertebrae, a priori knowledge by means of statistical shape models (SSMs) is often incorporated. One of the main challenges using SSMs is the solution of the correspondence problem. In this work we present a generic automated approach for solving the correspondence problem for vertebrae. We determine two closed loops on a reference shape and propagate them consistently to the remaining shapes of the training set. Then every shape is cut along these loops and parameterized to a rectangle. There, we optimize a novel combined energy to establish the correspondences and to reduce the unavoidable area and angle distortion. Finally, we present an adaptive resampling method to achieve a good shape representation. A qualitative and quantitative evaluation shows that using our method we can generate SSMs of higher quality than the ICP approach.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2011 |
| Creators: | Becker, Meike ; Kirschner, Matthias ; Fuhrmann, Simon ; Wesarg, Stefan |
| Type of entry: | Bibliographie |
| Title: | Automatic Construction of Statistical Shape Models for Vertebrae |
| Language: | English |
| Date: | 2011 |
| Publisher: | Springer, Berlin; Heidelberg; New York |
| Series: | Lecture Notes in Computer Science (LNCS); 6892 |
| Event Title: | Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011: Part II |
| DOI: | 10.1007/978-3-642-23629-7_61 |
| Abstract: | For segmenting complex structures like vertebrae, a priori knowledge by means of statistical shape models (SSMs) is often incorporated. One of the main challenges using SSMs is the solution of the correspondence problem. In this work we present a generic automated approach for solving the correspondence problem for vertebrae. We determine two closed loops on a reference shape and propagate them consistently to the remaining shapes of the training set. Then every shape is cut along these loops and parameterized to a rectangle. There, we optimize a novel combined energy to establish the correspondences and to reduce the unavoidable area and angle distortion. Finally, we present an adaptive resampling method to achieve a good shape representation. A qualitative and quantitative evaluation shows that using our method we can generate SSMs of higher quality than the ICP approach. |
| Uncontrolled Keywords: | Forschungsgruppe Medical Computing (MECO), Statistical shape models (SSM), 3D Model segmentation, Point correspondence, Cutting, Surface parameterization |
| Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Interactive Graphics Systems |
| Date Deposited: | 12 Nov 2018 11:16 |
| Last Modified: | 12 Nov 2018 11:16 |
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