Robust Liver Segmentation with Deep Learning Across DCE-MRI Contrast Phases
Author:
Publisher
Springer Fachmedien Wiesbaden
Link
https://link.springer.com/content/pdf/10.1007/978-3-658-36932-3_3
Reference9 articles.
1. Bilic P et al. The liver tumor segmentation benchmark (LiTS). arXiv e-prints. 2019. arXiv:1901.04056.
2. Roberts LR, Sirlin CB, Zaiem F, Almasri J, Prokop LJ, Heimbach JK et al. Imaging for the diagnosis of hepatocellular carcinoma: a systematic review and meta-analysis. Hepatology. 2018;67(1):401–21.
3. Chlebus G, Schenk A. Automatic liver and tumor segmentation in late-phase MRI using fully convolutional neural networks. Procs CURAC. 2018:195–200.
4. Winther H, Hundt C, Ringe KI, Wacker FK, Schmidt B, Jürgens J et al. A 3D deep neural network for liver volumetry in 3T contrast-enhanced MRI. RoFo. 2021;193(3):305–14.
5. Strehlow J, Spahr N, Rühaak J, Laue H, Abolmaali N, Preusser T et al. Landmark-based evaluation of a deformable motion correction for DCE-MRI of the liver. Int J Comput Assist Radiol Surg. 2018;13(4):597–606.
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