A highly densed deep neural architecture for classification of the multi-organs in fetal ultrasound scans
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-09148-x.pdf
Reference38 articles.
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2. Cai Y, Droste R, Sharma H, Chatelain P, Drukker L, Papageorghiou AT, Noble JA (2020) Spatio-temporal visual attention modelling of standard biometry plane-finding navigation. Med Image Anal 65:101762
3. Cai Y, Sharma H, Chatelain P, Noble JA (2018) Multi-task sonoeyenet: detection of fetal standardized planes assisted by generated sonographer attention maps. In: Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part I, pp. 871–879. Springer
4. Chen L, Bentley P, Mori K, Misawa K, Fujiwara M, Rueckert D (2019) Self-supervised learning for medical image analysis using image context restoration. Med Image Anal 58:101539
5. Dozen A, Komatsu M, Sakai A, Komatsu R, Shozu K, Machino H, Yasutomi S, Arakaki T, Asada K, Kaneko S et al (2020) Image segmentation of the ventricular septum in fetal cardiac ultrasound videos based on deep learning using time-series information. Biomolecules 10(11):1526
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