Dynamic Voting in Multi-view Learning for Radiomics Applications-Reference-Cited by-同舟云学术

Dynamic Voting in Multi-view Learning for Radiomics Applications

Published:2018 Issue: Volume: Page:32-41
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Cao Hongliu,Bernard Simon,Heutte Laurent,Sabourin Robert

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-97785-0_4

Reference19 articles.

1. Cao, H., Bernard, S., Heutte, L., Sabourin, R.: Dissimilarity-based representation for radiomics applications. ICPRAI 2018, arXiv:1803.04460 (2018)

2. Sorensen, L., Shaker, S.B., De Bruijne, M.: Quantitative analysis of pulmonary emphysema using local binary patterns. IEEE Trans. Med. Imaging 29(2), 559–569 (2010)

3. Sluimer, I., Schilham, A., Prokop, M., Van Ginneken, B.: Computer analysis of computed tomography scans of the lung: a survey. IEEE Trans. Med. Imaging 25(4), 385–405 (2006)

4. Lambin, P., et al.: Radiomics: extracting more information from medical images using advanced feature analysis. Eur. J. Cancer 48(4), 441–446 (2012)

5. Kumar, V., et al.: Radiomics: the process and the challenges. Magn. Reson. Imaging 30(9), 1234–1248 (2012)

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