Comparison of CNN Fusion Strategies for Left Ventricle Segmentation from Multi-modal MRI-Reference-Cited by-同舟云学术

Comparison of CNN Fusion Strategies for Left Ventricle Segmentation from Multi-modal MRI

Published:2023 Issue: Volume: Page:265-273
ISSN:0302-9743
Container-title:Functional Imaging and Modeling of the Heart
language:
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Author:

Ouadah Cylia^ORCID,Hadadi Azadeh^ORCID,Lalande Alain^ORCID,Leclerc Sarah^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-35302-4_27

Reference18 articles.

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3. Bernard, O., et al.: Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved? IEEE Trans. Med. Imaging 37(11), 2514–2525 (2018)

4. Lalande, A., et al.: Deep learning methods for automatic evaluation of delayed enhancement-MRI. The results of the EMIDEC challenge. Med. Imaging Anal. 79, 102428 (2022). https://doi.org/10.1016/j.media.2022.102428

5. Karim, R., et al.: Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late gadolinium enhancement MR images. Med. Image Anal. 30, 95–107 (2016). https://doi.org/10.1016/j.media.2016.01.004

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