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Self-aligning manifolds for matching disparate medical image datasets

Baumgartner CF, Gomez A, Koch LM, Housden JR, Kolbitsch C, McClelland JR, Rueckert D, King AP (2015)

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Publication Type: Conference contribution

Publication year: 2015

Journal

Publisher: Springer Verlag

Book Volume: 9123

Pages Range: 363-374

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: Isle of Skye, GBR

DOI: 10.1007/978-3-319-19992-4_28

Abstract

Manifold alignment can be used to reduce the dimensionality of multiple medical image datasets into a single globally consistent lowdimensional space. This may be desirable in a wide variety of problems, from fusion of different imaging modalities for Alzheimer’s disease classification to 4DMR reconstruction from 2D MR slices. Unfortunately, most existing manifold alignment techniques require either a set of prior correspondences or comparability between the datasets in high-dimensional space, which is often not possible. We propose a novel technique for the ‘self-alignment’ of manifolds (SAM) from multiple dissimilar imaging datasets without prior correspondences or inter-dataset image comparisons. We quantitatively evaluate the method on 4DMR reconstruction from realistic, synthetic sagittal 2D MR slices from 6 volunteers and real data from 4 volunteers. Additionally, we demonstrate the technique for the compounding of two free breathing 3D ultrasound views from one volunteer. The proposed method performs significantly better for 4DMR reconstruction than state-of-the-art image-based techniques.

Involved external institutions

How to cite

APA:

Baumgartner, C.F., Gomez, A., Koch, L.M., Housden, J.R., Kolbitsch, C., McClelland, J.R.,... King, A.P. (2015). Self-aligning manifolds for matching disparate medical image datasets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 363-374). Isle of Skye, GBR: Springer Verlag.

MLA:

Baumgartner, Christian F., et al. "Self-aligning manifolds for matching disparate medical image datasets." Proceedings of the 24th International Conference on Information Processing in Medical Imaging, IPMI 2015, Isle of Skye, GBR Springer Verlag, 2015. 363-374.

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