Abstract
We propose a method of registering 3D images in which many regions have been segmented and labelled. Images in which some regions have been labelled can be registered by generating a vector valued image with a number of planes, one for each individual label class, and applying registration algorithms to the multi-plane images [1]. However, when there are many labels such an approach can lead to unpractically large images. We demonstrate that good results can be obtained by mapping each label value to a vector in a low dimensional space and applying a multi-plane registration algorithm to the resulting vector image. For the approach to work well, the vectors used for each label should be well separated, and chosen in such a way that there is minimal confusion between them. We demonstrate the method by using it to construct statistical shape models by applying a groupwise alignment method to a set of richly labelled 3D brain images. © 2006 IEEE.
Original language | English |
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Title of host publication | 2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings|IEEE Int. Symp. Biomed. Imag. Nano Macro Proc. |
Pages | 868-871 |
Number of pages | 3 |
Volume | 2006 |
Publication status | Published - 2006 |
Event | 2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Arlington, VA Duration: 1 Jul 2006 → … |
Conference
Conference | 2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro |
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City | Arlington, VA |
Period | 1/07/06 → … |