Conference paper
Multi-region Statistical Shape Model for Cochlear Implantation
Pompeu Fabra University1
Department of Applied Mathematics and Computer Science, Technical University of Denmark2
Visual Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark3
Scientific Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark4
Statistical shape models are commonly used to analyze the variability between similar anatomical structures and their use is established as a tool for analysis and segmentation of medical images. However, using a global model to capture the variability of complex structures is not enough to achieve the best results.
The complexity of a proper global model increases even more when the amount of data available is limited to a small number of datasets. Typically, the anatomical variability between structures is associated to the variability of their physiological regions. In this paper, a complete pipeline is proposed for building a multi-region statistical shape model to study the entire variability from locally identified physiological regions of the inner ear.
The proposed model, which is based on an extension of the Point Distribution Model (PDM), is built for a training set of 17 high-resolution images (24.5 μm voxels) of the inner ear. The model is evaluated according to its generalization ability and specificity. The results are compared with the ones of a global model built directly using the standard PDM approach.
The evaluation results suggest that better accuracy can be achieved using a regional modeling of the inner ear.
Language: | English |
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Publisher: | SPIE - International Society for Optical Engineering |
Year: | 2016 |
Pages: | 97840T-97840T-8 |
Proceedings: | SPIE Medical Imaging 2016 |
Series: | Proceedings of Spie - the International Society for Optical Engineering |
ISBN: | 1510600191 and 9781510600195 |
ISSN: | 24109045 , 16057422 , 1996756x and 0277786x |
Types: | Conference paper |
DOI: | 10.1117/12.2213305 |
ORCIDs: | Kjer, H. Martin |