Multi-domain abdomen image alignment based on multi-scale diffeomorphic jointed network

Zhengwei LU; Yong WANG; Qiu GUAN; Yizhou CHEN; Dongchun LIU; Xinli XU

doi:10.1007/s11801-022-2052-3

[1] LIU F, CAI J, HUO Y, et al. JSSR:a joint synthesis, segmentation, and registration system for 3D multi-modal image alignment of large-scale pathological CT scans[C]//European Conference on Computer Vision 2020, August 23-28, 2020, Glasgow, UK. Berlin, Heidelberg:Springer-Verlag, 2020:257-274.

[2] HUIJSKENS S C, VAN DIJK I W E M, VISSER J, et al. Abdominal organ position variation in children during image-guided radiotherapy[J]. Radiation oncology, 2018, 13(1):1-9.

[3] ZHANG Y, JIANG F, SHEN R. Region-based face alignment with convolution neural network cascade[C]//24th International Conference on Neural Information Processing, November 14-18, 2017, Guangzhou, China. Berlin, Heidelberg:Springer-Verlag, 2017:300-309.

[4] JADERBERG M, SIMONYAN K, ZISSERMAN A. Spatial transformer networks[J]. Advances in neural information processing systems, 2015, 28:2017-2025.

[5] CAO X, YANG J, GAO Y, et al. Dual-core steered non-rigid registration for multi-modal images via bi-directional image synthesis[J]. Medical image analysis, 2017, 41:18-31.

[6] FAN J, CAO X, WANG Q, et al. Adversarial learning for mono- or multi-domain registration[J]. Medical image analysis, 2019, 58:101545.

[7] DUBOST F, DE BRUIJNE M, NARDIN M, et al. Multi-atlas image registration of clinical data with automated quality assessment using ventricle segmentation[ J]. Medical image analysis, 2020, 63:101698.

[8] BLENDOWSKI M, HANSEN L, HEINRICH M P. Weakly-supervised learning of multi-modal features for regularised iterative descent in 3D image registration[J]. Medical image analysis, 2021, 67:101822.

[9] TANG T, GUAN Q, WU Y. Support vector machine incremental learning triggered by wrongly predicted samples[J]. Optoelectronics letters, 2018, 14(3):232-235.

[10] VERCAUTEREN T, PENNEC X, PERCHANT A, et al. Diffeomorphic demons:efficient non-parametric image registration[J]. Neuroimage, 2009, 45(1):S61-S72.

[11] BEG M F, MILLER M I, TROUVé A, et al. Computing large deformation metric mappings via geodesic flows of diffeomorphisms[J]. International journal of computer vision, 2005, 61(2):139-157.

[12] GOODFELLOW I, POUGET-ABADIE J, MIRZA M, et al. Generative adversarial nets[J]. Advances in neural information processing systems, 2014, 27:2672-2680.

[13] ZHU J Y, PARK T, ISOLA P, et al. Unpaired image-to-image translation using cycle-consistent adversarial networks[C]//Proceedings of the IEEE International Conference on Computer Vision, October 22-29, 2017, Venice, Italy. New York:IEEE, 2017:2223-2232.

[14] LIU M Y, BREUEL T, KAUTZ J. Unsupervised image-to-image translation networks[J]. Advances in neural information processing systems, 2017, 30:700-708.

[15] QIN C, SHI B, LIAO R, et al. Unsupervised deformable registration for multi-modal images via disentangled representations[C]//International Conference on Information Processing in Medical Imaging, June 2, 2019, Hong Kong, China. Berlin, Heidelberg:Springer-Verlag, 2019:249-261.

[16] WEI D, AHMAD S, HUO J, et al. SLIR:synthesis, localization, inpainting, and registration for image-guided thermal ablation of liver tumors[J]. Medical image analysis, 2020, 65:101763.

[17] XU Z, LUO J, YAN J, et al. Adversarial uni-and multi-modal stream networks for multimodal image registration[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention, October 4-8, 2020, Lima, Peru. Berlin, Heidelberg :Springer-Verlag, 2020:222-232.

[18] ZHOU B, AUGENFELD Z, CHAPIRO J, et al. Anatomy-guided multimodal registration by learning segmentation without ground truth:application to intraprocedural CBCT/MR liver segmentation and registration[J]. Medical image analysis, 2021, 71:102041.

[19] BALAKRISHNAN G, ZHAO A, SABUNCU M R, et al. Voxelmorph:a learning framework for deformable medical image registration[J]. IEEE transactions on medical imaging, 2019, 38(8):1788-1800.

[20] ARAR M, GINGER Y, DANON D, et al. Unsupervised multi-modal image registration via geometry preserving image-to-image translation[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 16-18, 2020, Seattle, WA, USA. New York:IEEE, 2020:13410-13419.

[21] ZHAO S, DONG Y, CHANG E I, et al. Recursive cascaded networks for unsupervised medical image registration[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision, October 27-November 2, 2019, Seoul, Korea (South). New York:IEEE, 2019: 10600-10610.

[22] KIM B, KIM D H, PARK S H, et al. Cyclemorph:cycle consistent unsupervised deformable image registration[J]. Medical image analysis, 2021, 71:102036.

[23] HEUSEL M, RAMSAUER H, UNTERTHINER T, et al. GANs trained by a two time-scale update rule converge to a local nash equilibrium[J]. Advances in neural information processing systems, 2017, 30:6626-6637.

[24] CHEN Y, LU Z, YANG X H, et al. Multi-domain abdomen image alignment based on joint network of registration and synthesis[C]//International Conference on Neural Information Processing, December 8-12, 2021, Bali, Indonesia. Berlin, Heidelberg:Springer-Verlag, 2021:334-344.

[25] SZEGEDY C, VANHOUCKE V, IOFFE S, et al. Rethinking the inception architecture for computer vision[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June 16-July 1, 2016, Las Vegas, USA. New York:IEEE, 2016:2818-2826.