Ravikumar, N, Gooya, A, Frangi, AF orcid.org/0000-0002-2675-528X et al. (1 more author) (2017) Generalised coherent point drift for group-wise registration of multi-dimensional point sets. In: Lecture Notes in Computer Science. Medical Image Computing and Computer Assisted Intervention - MICCAI 2017. 20th International Conference, 10-14 Sep 2017, Quebec, Canada. Springer , pp. 309-316. ISBN 9783319661810
Abstract
In this paper we propose a probabilistic approach to group-wise registration of unstructured high-dimensional point sets. We focus on registration of generalised point sets which encapsulate both the positions of points on surface boundaries and corresponding normal vectors describing local surface geometry. Richer descriptions of shape can be especially valuable in applications involving complex and intricate variations in geometry, where spatial position alone is an unreliable descriptor for shape registration. A hybrid mixture model combining Student’s t and Von-Mises-Fisher distributions is proposed to model position and orientation components of the point sets, respectively. A group-wise rigid and non-rigid registration framework is then formulated on this basis. Two clinical data sets, comprising 27 brain ventricle and 15 heart shapes, were used to assess registration accuracy. Significant improvement in accuracy and anatomical validity of the estimated correspondences was achieved using the proposed approach, relative to state-of-the-art point set registration approaches, which consider spatial positions alone.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer International Publishing AG 2017. This is an author produced version of a conference paper published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Medical and Biological Engineering (iMBE) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Apr 2019 10:17 |
Last Modified: | 30 Apr 2019 10:17 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/978-3-319-66182-7_36 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:145282 |