References
- Avants BB, Epstein CL, Grossman M, Gee JC. 2008. Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med Image Anal. 12(1):26–41. doi:https://doi.org/10.1016/j.media.2007.06.004.
- Avants BB, Tustison NJ, Song G, Cook PA, Klein A, Gee JC. 2011. A reproducible evaluation of ANTs similarity metric performance in brain image registration. Neuroimage. 54(3):2033–2044. doi:https://doi.org/10.1016/j.neuroimage.2010.09.025.
- Dice LR. 1945. Measures of the amount of ecologic association between species. Ecology. 26(3):297–302. doi:https://doi.org/10.2307/1932409.
- Dickinson L, Hu Y, Ahmed HU, Allen C, Kirkham AP, Emberton M, Barratt D. 2013. Image-directed, tissue-preserving focal therapy of prostate cancer: a feasibility study of a novel deformable magnetic resonance-ultrasound (MR-US) registration system. BJU Int. 112(5):594–601. doi:https://doi.org/10.1111/bju.12223.
- Fedorov A, Beichel R, Kalpathy-Cramer J, Finet J, J-c F-R, Pujol S, Bauer C, Jennings D, Fennessy F, Sonka M, et al. 2012. 3D slicer as an image computing platform for the quantitative imaging network. Magn Reson Imaging. 30:1323–1341. doi:https://doi.org/10.1016/j.mri.2012.05.001.
- Ö Ç, Abdulkadir A, Lienkamp S, Brox T, Ronneberger O 2016. 3D U-Net: learning dense volumetric segmentation from sparse annotation. In: 2016 International Conference on Medical Image Computing and Computer-Assisted Intervention; Oct 17; Springer, Cham.; p. 424–432.
- Hu Y, Gibson E, Vercauteren T, Ahmed HU, Emberton M, Moore CM, Noble JA, Barratt DC 2017. Intraoperative organ motion models with an ensemble of conditional generative adversarial networks. In: 2017 International Conference on Medical Image Computing and Computer-Assisted Intervention; Sep 10; Springer, Cham.: p. 368–376.
- Isola P, Zhu J, Zhou T, Efros AA 2017. Image-to-image translation with conditional adversarial networks. In: 2017 IEEE Conf Comput Vis Pattern Recognit.; July 21; Honolulu, Hawaii, USA: p. 1125–1134
- Jaderberg M, Simonyan K, Zisserman A, Koray K. 2015. Spatial Transformer Networks. arXiv preprint arXiv: 1506.02025
- Kingma D, Ba J 2014. Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980.
- Li J, Fang F, Mei K, Zhang G 2018. Multi-scale residual network for image super-resolution: 15th European Conference, Munich, Germany, Sep. 8-14, 2018, Proceedings, Part VIII; p. 517–532.
- Mansilla L, Milone DH, Ferrante E. 2020. Learning deformable registration of medical images with anatomical constraints. Neural Networks. 124:269–279. doi:https://doi.org/10.1016/j.neunet.2020.01.023.
- Mirza M, Osindero S 2014. Conditional generative adversarial nets. arXiv preprint arXiv:1411.1784
- Verpalen IM, Van ‘T Veer-ten Kate M, De Boer E, Rd VDH, Jm S, Jr D, Franx A, Lw B, Ctw M, Mf B. 2020. Development and clinical evaluation of a 3-step modified manipulation protocol for MRI-guided high-intensity focused ultrasound of uterine fibroids. Eur Radiol. 30(7):3869–3878. doi:https://doi.org/10.1007/s00330-020-06780-2.
- Wang Y, Cheng J-Z, Ni D, Lin M, Qin J, Luo X, Xu M, Xie X, Heng P. 2016. Towards personalized statistical deformable model and hybrid point matching for robust MR-TRUS registration. IEEE Trans Med Imaging. 35(2):589–604. doi:https://doi.org/10.1109/TMI.2015.2485299.
- Yoo JC, Han T. 2009. Fast normalized cross-correlation. Circuits, Syst Signal Process. 28:819–843. doi:https://doi.org/10.1007/s00034-009-9130-7.
- Yoo TK, Choi JY, Kim HK. 2020. A generative adversarial network approach to predicting postoperative appearance after orbital decompression surgery for thyroid eye disease. Comput Biol Med. 118:103628. doi:https://doi.org/10.1016/j.compbiomed.2020.103628.