A Kernelized Multi-level Localization Method for Flexible Shape Modeling with Few Training Data-Reference-Cited by-同舟云学术

A Kernelized Multi-level Localization Method for Flexible Shape Modeling with Few Training Data

Published:2020 Issue: Volume: Page:765-775
ISSN:0302-9743
Container-title:Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
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Author:

Wilms Matthias,Ehrhardt Jan,Forkert Nils D.

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-59719-1_74

Reference29 articles.

1. Alvarez, M.A., Rosasco, L., Lawrence, N.D., et al.: Kernels for vector-valued functions: a review. Found. Trends Mach. Learn. 4(3), 195–266 (2012)

2. Avants, B., Tustison, N.: ANTs/ANTsR brain templates (2014). https://doi.org/10.6084/m9.figshare.915436.v2

3. Cootes, T., Taylor, C., Cooper, D., Graham, J.: Active shape models-their training and application. CVIU 61(1), 38–59 (1995)

4. Cootes, T.F., Taylor, C.J.: Data driven refinement of active shape model search. In: British Machine Vision Conference - BMVC, 1996, pp. 1–10 (1996)

5. Davies, R., Twining, C., Cootes, T., Waterton, J., Taylor, C.: A minimum description length approach to statistical shape modeling. IEEE Trans. Med. Imaging 21(5), 525–537 (2002)

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