Automated Segmentation of the Right Ventricle from 3D Echocardiography Using Labels from Cardiac Magnetic Resonance Imaging-Reference-Cited by-同舟云学术

Automated Segmentation of the Right Ventricle from 3D Echocardiography Using Labels from Cardiac Magnetic Resonance Imaging

Published:2024 Issue: Volume: Page:119-129
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:en
Short-container-title:

Author:

Dillon Joshua R.,Zhao Debbie,Gamage Thiranja P. Babarenda,Quill Gina M.,Wang Vicky Y.,Edwards Nicola C.,Sutton Timothy M.,Lowe Boris S.,Legget Malcolm E.,Doughty Robert N.,Young Alistair A.,Nash Martyn P.

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-52448-6_12

Reference19 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. Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: DeepLab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. IEEE Trans. Pattern Anal. Mach. Intell. 40(4), 834–848 (2018)

5. Danudibroto, A., Bersvendsen, J., Mirea, O., Gerard, O., D’hooge, J., Samset, E.: Image-based temporal alignment of echocardiographic sequences. In: Duric, N., Heyde, B. (eds.) Medical Imaging 2016: Ultrasonic Imaging and Tomography. vol. 9790, p. 97901G. International Society for Optics and Photonics, SPIE (2016). https://doi.org/10.1117/12.2216192