Adversarial learning for deformable registration of brain MR image using a multi-scale fully convolutional network

Biomedical Signal Processing and Control - Tập 53 - Trang 101562 - 2019
Luwen Duan1,2, Gang Yuan2, Lun Gong3, Tianxiao Fu4, Xiaodong Yang2, Xinjian Chen5, Jian Zheng2
1School of Biomedical Engineering, University of Science and Technology of China, Hefei, 230000, China
2Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China
3The Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, 300072, China
4Department of Radiation Oncology, The First Affiliated Hospital of Soochow University, Suzhou 215006, China
5School of Electronics and Information Engineering, Soochow University, Suzhou 215006, China

Tài liệu tham khảo

Aljabar, 2009, Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracy, Neuroimage, 46, 726, 10.1016/j.neuroimage.2009.02.018 Lee, 2008, Assessment of parotid gland dose changes during head and neck cancer radiotherapy using daily megavoltage computed tomography and deformable image registration, Int. J. Radiat. Oncol. Biol. Phys., 71, 1563, 10.1016/j.ijrobp.2008.04.013 Collins, 2017, Improving registration robustness for image-guided liver surgery in a novel human-to-phantom data framework, IEEE Trans.Med. Imaging, 36, 1502, 10.1109/TMI.2017.2668842 Holden, 2008, A review of geometric transformations for nonrigid body registration, IEEE Trans. Med. Imaging, 27, 111, 10.1109/TMI.2007.904691 Rueckert, 1999, Nonrigid registration using free-form deformations: application to breast MR images, IEEE Trans. Med. Imaging, 18, 712, 10.1109/42.796284 Vercauteren, 2009, Diffeomorphic demons: efficient non-parametric image registration, NeuroImage, 45, S61, 10.1016/j.neuroimage.2008.10.040 Rivaz, 2014, Nonrigid registration of ultrasound and MRI using contextual conditioned mutual information, IEEE Trans. Med. Imaging, 33, 708, 10.1109/TMI.2013.2294630 Zhuang, 2011, A nonrigid registration framework using spatially encoded mutual information and free-form deformations, IEEE Trans.Med. Imaging, 30, 1819, 10.1109/TMI.2011.2150240 Gong, 2018, Non-rigid image registration using spatially region-weighted correlation ratio and GPU-acceleration, IEEE J. Biomed. Health Inform. Shen, 2002, HAMMER: hierarchical attribute matching mechanism for elastic registration, IEEE Trans. Med. Imaging, 21, 1421, 10.1109/TMI.2002.803111 Zheng, 2011, Salient feature region: a new method for retinal image registration, IEEE Trans. Inf. Technol. Biomed., 15, 221, 10.1109/TITB.2010.2091145 Zhu, 2016, Self-similarity inspired local descriptor for non-rigid multi-modal image registration, Inf. Sci. (Ny), 372, 16, 10.1016/j.ins.2016.08.031 Ou, 2011, DRAMMS: deformable registration via attribute matching and mutual-saliency weighting, Med. Image Anal., 15, 622, 10.1016/j.media.2010.07.002 El Rube, 2009, Image registration based on multi-scale SIFT for remote sensing images, Proc. ICSPCS, 1 Nie, 2018, 3-D fully convolutional networks for multimodal isointense infant brain image segmentation, IEEE Trans. Cybern. Mohan, 2018, MRI based medical image analysis: survey on brain tumor grade classification, Biomed. Signal Process. Control, 39, 139, 10.1016/j.bspc.2017.07.007 Jin, 2018, A deep 3D residual CNN for false positive reduction in pulmonary nodule detection, Med. Phys., 10.1002/mp.12846 Wu, 2016, Scalable high performance image registration framework by unsupervised deep feature representations learning, IEEE Trans. Biomed. Eng., 63, 1505, 10.1109/TBME.2015.2496253 Kearney, 2018, An unsupervised convolutional neural network-based algorithm for deformable image registration, Phys. Med. Biol., 10.1088/1361-6560/aada66 Yang, 2017, Quicksilver: fast predictive image registration–a deep learning approach, NeuroImage, 158, 378, 10.1016/j.neuroimage.2017.07.008 Sokooti, 2017, Nonrigid image registration using multi-scale 3D convolutional neural networks, Proc. Int. Conf. Med. Image Comput. Comput.-Assisted Intervention Cao, 2018, Deformable image registration using cue-aware deep regression network, IEEE Trans. Biomed. Eng., 10.1109/TBME.2018.2822826 Fan, 2018, BIRNet: brain image registration using dual-supervised fully convolutional networks, Proc. IEEE CVPR Rohé, 2017, SVF-net: learning deformable image registration using shape matching, 266 de Vos, 2017, End-to-End unsupervised deformable image registration with a convolutional neural network, Proc. DLMIA, 204 Shan, 2017 Balakrishnan, 2018, An unsupervised learning model for deformable medical image registration, Proc. IEEE CVPR, 9252 Li, 2018, Non-rigid image registration using self-supervised fully convolutional networks without training data, Proc. IEEE ISBI, 1075 Zhou, 2016, Registration of pre- and postresection ultrasound volumes with noncorresponding regions in neurosurgery, IEEE J. Biomed. Health Inform., 20, 1240, 10.1109/JBHI.2016.2554122 Goodfellow, 2014, Generative adversarial nets, Adv. Neural Inf. Process. Syst., 2672 Radford, 2015 Nie, 2018, Medical image synthesis with deep convolutional adversarial networks, IEEE Trans. Biomed. Eng., 10.1109/TBME.2018.2814538 Moeskops, 2017, Adversarial training and dilated convolutions for brain MRI segmentation, Proc. DLMIA, 56 Ronneberger, 2015, U-net: convolutional networks for biomedical image segmentation, 234 Zeiler, 2011, Adaptive deconvolutional networks for mid and high level feature learning Ren, 2017, Faster R-CNN: towards real-time object detection with region proposal networks, IEEE Trans. Pattern Anal. MachIntell., 39, 1137, 10.1109/TPAMI.2016.2577031 Fischl, 2012, Freesurfer, Neuroimage, 62, 774, 10.1016/j.neuroimage.2012.01.021 Tustison, 2010, N4ITK: improved N3 Bias correction, IEEE Trans. Med. Imaging, 10.1109/TMI.2010.2046908 Shattuck, 2008, Construction of a 3D probabilistic atlas of human cortical structures, NeuroImage, 39, 1064, 10.1016/j.neuroimage.2007.09.031 Klein, 2009, Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration, NeuroImage, 46, 786, 10.1016/j.neuroimage.2008.12.037 Chollet, 2015 Abadi, 2016 Avants, 2008, Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain, MedIA, 12, 26 Ashburner, 2011, Diffeomorphic registration using geodesic shooting and Gauss–Newton optimisation, NeuroImage, 55, 954, 10.1016/j.neuroimage.2010.12.049 Vercauteren, 2009, Diffeomorphic demons: efficient non-parametric image registration, NeuroImage, 45, 61, 10.1016/j.neuroimage.2008.10.040 Suh, 2012, CT-PET weighted image fusion for separately scanned whole body rat, Med. Phys., 39, 533, 10.1118/1.3672167 Arsigny, 2006, A logeuclidean framework for statistics on diffeomorphisms, 924