Table of Contents

• SVoRT: Iterative Transformer for Slice-to-Volume Registration in Fetal Brain MRIJunshen Xu, Daniel Moyer, Patricia Ellen Grant, Polina Golland, Juan Eugenio Iglesias, Elfar Adalsteinsson. 3-13 [doi]
• Double-Uncertainty Guided Spatial and Temporal Consistency Regularization Weighting for Learning-Based Abdominal RegistrationZhe Xu, Jie Luo 0003, Donghuan Lu, Jiangpeng Yan, Sarah F. Frisken, Jayender Jagadeesan, William M. Wells III, Xiu Li, Yefeng Zheng 0001, Raymond Kai-Yu Tong. 14-24 [doi]
• Unsupervised Deformable Image Registration with Absent Correspondences in Pre-operative and Post-recurrence Brain Tumor MRI ScansTony C. W. Mok, Albert C. S. Chung. 25-35 [doi]
• On the Dataset Quality Control for Image Registration EvaluationJie Luo 0003, Guangshen Ma, Nazim Haouchine, Zhe Xu, Yixin Wang, Tina Kapur, Lipeng Ning, William M. Wells III, Sarah F. Frisken. 36-45 [doi]
• Dual-Branch Squeeze-Fusion-Excitation Module for Cross-Modality Registration of Cardiac SPECT and CTXiongchao Chen, Bo Zhou 0009, Huidong Xie, Xueqi Guo, Jiazhen Zhang, Albert J. Sinusas, John A. Onofrey, Chi Liu. 46-55 [doi]
• Embedding Gradient-Based Optimization in Image Registration NetworksHuaqi Qiu, Kerstin Hammernik, Chen Qin, Chen Chen 0042, Daniel Rueckert. 56-65 [doi]
• ContraReg: Contrastive Learning of Multi-modality Unsupervised Deformable Image RegistrationNeel Dey, Jo Schlemper, Seyed Sadegh Mohseni Salehi, Bo Zhou 0009, Guido Gerig, Michal Sofka. 66-77 [doi]
• Swin-VoxelMorph: A Symmetric Unsupervised Learning Model for Deformable Medical Image Registration Using Swin TransformerYongpei Zhu, Shi Lu. 78-87 [doi]
• Non-iterative Coarse-to-Fine Registration Based on Single-Pass Deep Cumulative LearningMingyuan Meng, Lei Bi 0001, Dagan Feng, Jinman Kim. 88-97 [doi]
• DSR: Direct Simultaneous Registration for Multiple 3D ImagesZhehua Mao, Liang Zhao 0003, Shoudong Huang, Yiting Fan, Alex Pui-Wai Lee. 98-107 [doi]
• Multi-modal Retinal Image Registration Using a Keypoint-Based Vessel Structure Aligning NetworkAline Sindel, Bettina Hohberger, Andreas K. Maier, Vincent Christlein. 108-118 [doi]
• A Deep-Discrete Learning Framework for Spherical Surface RegistrationMohamed A. Suliman, Logan Z. J. Williams, Abdulah Fawaz, Emma C. Robinson. 119-129 [doi]
• Privacy Preserving Image RegistrationRiccardo Taiello, Melek Önen, Olivier Humbert, Marco Lorenzi. 130-140 [doi]
• Deformer: Towards Displacement Field Learning for Unsupervised Medical Image RegistrationJiashun Chen, Donghuan Lu, Yu Zhang, Dong Wei 0004, Munan Ning, Xinyu Shi, Zhe Xu, Yefeng Zheng 0001. 141-151 [doi]
• End-to-End Multi-Slice-to-Volume Concurrent Registration and Multimodal GenerationAmaury Leroy, Marvin Lerousseau, Théophraste Henry, Alexandre Cafaro, Nikos Paragios, Vincent Grégoire, Eric Deutsch. 152-162 [doi]
• Fast Spherical Mapping of Cortical Surface Meshes Using Deep Unsupervised LearningFenqiang Zhao, Zhengwang Wu, Li Wang 0026, Weili Lin, Gang Li. 163-173 [doi]
• Learning-Based US-MR Liver Image Registration with Spatial PriorsQi Zeng 0004, Shahed K. Mohammed, Emily H. T. Pang, Caitlin Schneider, Mohammad Honarvar, Julio Lobo, Changhong Hu, James Jago, Gary C. Ng, Robert Rohling, Septimiu E. Salcudean. 174-184 [doi]
• Unsupervised Deep Non-rigid Alignment by Low-Rank Loss and Multi-input AttentionTakanori Asanomi, Kazuya Nishimura, Heon Song, Junya Hayashida, Hiroyuki Sekiguchi, Takayuki Yagi, Imari Sato, Ryoma Bise. 185-195 [doi]
• Transformer Lesion TrackerWen Tang, Han Kang, Haoyue Zhang, Pengxin Yu, Corey W. Arnold, Rongguo Zhang. 196-206 [doi]
• LiftReg: Limited Angle 2D/3D Deformable RegistrationLin Tian, Yueh Z. Lee, Raúl San José Estépar, Marc Niethammer. 207-216 [doi]
• XMorpher: Full Transformer for Deformable Medical Image Registration via Cross AttentionJiacheng Shi, Yuting He, Youyong Kong, Jean-Louis Coatrieux, Huazhong Shu, Guanyu Yang, Shuo Li 0001. 217-226 [doi]
• Weakly-Supervised Biomechanically-Constrained CT/MRI Registration of the SpineBailiang Jian, Mohammad Farid Azampour, Francesca De Benetti, Johannes Oberreuter, Christina Bukas, Alexandra S. Gersing, Sarah C. Foreman, Anna-Sophia Dietrich, Jon Rischewski, Jan S. Kirschke, Nassir Navab, Thomas Wendler 0001. 227-236 [doi]
• Collaborative Quantization Embeddings for Intra-subject Prostate MR Image RegistrationZiyi Shen, Qianye Yang, Yuming Shen, Francesco Giganti, Vasilis Stavrinides, Richard E. Fan, Caroline M. Moore, Mirabela Rusu, Geoffrey A. Sonn, Philip H. S. Torr, Dean C. Barratt, Yipeng Hu. 237-247 [doi]
• Mesh-Based 3D Motion Tracking in Cardiac MRI Using Deep LearningQingjie Meng, Wenjia Bai, Tianrui Liu, Declan P. O'Regan, Daniel Rueckert. 248-258 [doi]
• Data-Driven Multi-modal Partial Medical Image Preregistration by Template Space Patch MappingDing Xia, Xi Yang 0017, Oliver van Kaick, Taichi Kin, Takeo Igarashi. 259-268 [doi]
• Global Multi-modal 2D/3D Registration via Local Descriptors LearningViktoria Markova, Matteo Ronchetti, Wolfgang Wein, Oliver Zettinig, Raphael Prevost. 269-279 [doi]
• Adapting the Mean Teacher for Keypoint-Based Lung Registration Under Geometric Domain ShiftsAlexander Bigalke, Lasse Hansen, Mattias P. Heinrich. 280-290 [doi]
• DisQ: Disentangling Quantitative MRI Mapping of the HeartChangchun Yang, Yidong Zhao, Lu Huang, Liming Xia, Qian Tao. 291-300 [doi]
• Learning Iterative Optimisation for Deformable Image Registration of Lung CT with Recurrent Convolutional NetworksFenja Falta, Lasse Hansen, Mattias P. Heinrich. 301-309 [doi]
• Electron Microscope Image Registration Using Laplacian Sharpening Transformer U-NetKunzi Xie, Yixing Yang, Maurice Pagnucco, Yang Song 0001. 310-319 [doi]
• Undersampled MRI Reconstruction with Side Information-Guided NormalisationXinwen Liu 0003, Jing Wang, Cheng Peng, Shekhar S. Chandra, Feng Liu 0005, S. Kevin Zhou. 323-333 [doi]
• Noise2SR: Learning to Denoise from Super-Resolved Single Noisy Fluorescence ImageXuanyu Tian, Qing Wu, Hongjiang Wei, Yuyao Zhang. 334-343 [doi]
• RPLHR-CT Dataset and Transformer Baseline for Volumetric Super-Resolution from CT ScansPengxin Yu, Haoyue Zhang, Han Kang, Wen Tang, Corey W. Arnold, Rongguo Zhang. 344-353 [doi]
• A Learnable Variational Model for Joint Multimodal MRI Reconstruction and SynthesisWanyu Bian, Qingchao Zhang, Xiaojing Ye, Yunmei Chen. 354-364 [doi]
• Autofocusing+: Noise-Resilient Motion Correction in Magnetic Resonance ImagingEkaterina Kuzmina, Artem Razumov, Oleg Y. Rogov, Elfar Adalsteinsson, Jacob White, Dmitry V. Dylov. 365-375 [doi]
• Tagged-MRI Sequence to Audio Synthesis via Self Residual Attention Guided Heterogeneous TranslatorXiaofeng Liu 0001, Fangxu Xing, Jerry L. Prince, Jiachen Zhuo, Maureen Stone, Georges El Fakhri, Jonghye Woo. 376-386 [doi]
• Only-Train-Once MR Fingerprinting for Magnetization Transfer Contrast QuantificationBeomgu Kang, Hye-Young Heo, HyunWook Park. 387-396 [doi]
• AutoGAN-Synthesizer: Neural Architecture Search for Cross-Modality MRI SynthesisXiaobin Hu, Ruolin Shen, Donghao Luo, Ying Tai, Chengjie Wang, Bjoern H. Menze. 397-409 [doi]
• Multi-scale Super-Resolution Magnetic Resonance Spectroscopic Imaging with Adjustable SharpnessSiyuan Dong, Gilbert Hangel, Wolfgang Bogner, Georg Widhalm, Karl Rössler, Siegfried Trattnig, Chenyu You, Robin A. de Graaf, John A. Onofrey, James S. Duncan. 410-420 [doi]
• Progressive Subsampling for Oversampled Data - Application to Quantitative MRIStefano B. Blumberg, Hongxiang Lin, Francesco Grussu, Yukun Zhou, Matteo Figini, Daniel C. Alexander. 421-431 [doi]
• 2 Quantification from Undersampled Magnetic Resonance Fingerprinting Data to Track Tracer Kinetics in Small Laboratory AnimalsYuning Gu, Yongsheng Pan, Zhenghan Fang, Jingyang Zhang, Peng Xue, Mianxin Liu, Yuran Zhu, Lei Ma, Charlie Androjna, Xin Yu, Dinggang Shen. 432-441 [doi]
• NAF: Neural Attenuation Fields for Sparse-View CBCT ReconstructionRuyi Zha, Yanhao Zhang, Hongdong Li. 442-452 [doi]
• UASSR: Unsupervised Arbitrary Scale Super-Resolution Reconstruction of Single Anisotropic 3D Images via Disentangled Representation LearningJiale Wang, Runze Wang, Rong Tao, Guoyan Zheng. 453-462 [doi]
• WavTrans: Synergizing Wavelet and Cross-Attention Transformer for Multi-contrast MRI Super-ResolutionGuangyuan Li, Jun Lyu, Chengyan Wang, Qi Dou, Jing Qin 0001. 463-473 [doi]
• DuDoCAF: Dual-Domain Cross-Attention Fusion with Recurrent Transformer for Fast Multi-contrast MR ImagingJun Lyu, Bin Sui, Chengyan Wang, Yapeng Tian, Qi Dou, Jing Qin 0001. 474-484 [doi]
• Weakly Supervised MR-TRUS Image Synthesis for Brachytherapy of Prostate CancerYunkui Pang, Xu Chen, Yunzhi Huang, Pew-Thian Yap, Jun Lian. 485-494 [doi]
• Domain-Adaptive 3D Medical Image Synthesis: An Efficient Unsupervised ApproachQingqiao Hu, Hongwei Li, Jianguo Zhang. 495-504 [doi]
• What Can We Learn About a Generated Image Corrupting Its Latent Representation?Agnieszka Tomczak, Aarushi Gupta, Slobodan Ilic, Nassir Navab, Shadi Albarqouni. 505-515 [doi]
• 3D CVT-GAN: A 3D Convolutional Vision Transformer-GAN for PET ReconstructionPinxian Zeng, Luping Zhou, Chen Zu, Xinyi Zeng, Zhengyang Jiao, Xi Wu 0004, Jiliu Zhou, Dinggang Shen, Yan Wang 0015. 516-526 [doi]
• Classification-Aided High-Quality PET Image Synthesis via Bidirectional Contrastive GAN with Shared Information MaximizationYuchen Fei, Chen Zu, Zhengyang Jiao, Xi Wu 0004, Jiliu Zhou, Dinggang Shen, Yan Wang 0015. 527-537 [doi]
• Swin Deformable Attention U-Net Transformer (SDAUT) for Explainable Fast MRIJiahao Huang, Xiaodan Xing, Zhifan Gao, Guang Yang 0006. 538-548 [doi]
• Low-Dose CT Reconstruction via Dual-Domain Learning and Controllable ModulationXinchen Ye, Zheng Sun, Rui Xu 0002, Zhihui Wang, Haojie Li. 549-559 [doi]
• Graph-Based Compression of Incomplete 3D Photoacoustic DataWeihang Liao, Yinqiang Zheng, Hiroki Kajita, Kazuo Kishi, Imari Sato. 560-570 [doi]
• 3-Net: Difficulty-Perceived Common-to-T1ce Semi-supervised Multimodal MRI Synthesis NetworkZiqi Huang, Li Lin 0006, Pujin Cheng, Kai Pan, Xiaoying Tang 0001. 571-581 [doi]
• Invertible Sharpening Network for MRI Reconstruction EnhancementSiyuan Dong, Eric Z. Chen, Lin Zhao 0004, Xiao Chen, Yikang Liu, Terrence Chen, Shanhui Sun. 582-592 [doi]
• Analyzing and Improving Low Dose CT Denoising Network via HU Level SlicingSutanu Bera, Prabir Kumar Biswas. 593-602 [doi]
• Spatio-Temporal Motion Correction and Iterative Reconstruction of In-Utero Fetal fMRIAthena Taymourtash, Hamza Kebiri, Ernst Schwartz, Karl-Heinz Nenning, Sébastien Tourbier, Gregor Kasprian, Daniela Prayer, Meritxell Bach Cuadra, Georg Langs. 603-612 [doi]
• Deep Filter Bank Regression for Super-Resolution of Anisotropic MR Brain ImagesSamuel W. Remedios, Shuo Han, Yuan Xue, Aaron Carass, Trac D. Tran, Dzung L. Pham, Jerry L. Prince. 613-622 [doi]
• Towards Performant and Reliable Undersampled MR Reconstruction via Diffusion Model SamplingCheng Peng, Pengfei Guo, S. Kevin Zhou, Vishal M. Patel, Rama Chellappa. 623-633 [doi]
• Patch-Wise Deep Metric Learning for Unsupervised Low-Dose CT DenoisingChanyong Jung, Joonhyung Lee, Sunkyoung You, Jong Chul Ye. 634-643 [doi]
• BMD-GAN: Bone Mineral Density Estimation Using X-Ray Image Decomposition into Projections of Bone-Segmented Quantitative Computed Tomography Using Hierarchical LearningYi Gu, Yoshito Otake, Keisuke Uemura, Mazen Soufi, Masaki Takao, Nobuhiko Sugano, Yoshinobu Sato. 644-654 [doi]
• Measurement-Conditioned Denoising Diffusion Probabilistic Model for Under-Sampled Medical Image ReconstructionYutong Xie, Quanzheng Li. 655-664 [doi]
• Orientation-Shared Convolution Representation for CT Metal Artifact LearningHong Wang, Qi Xie, Yuexiang Li, Yawen Huang, Deyu Meng, Yefeng Zheng 0001. 665-675 [doi]
• MRI Reconstruction by Completing Under-sampled K-space Data with Learnable Fourier InterpolationQiaoqiao Ding, Xiaoqun Zhang. 676-685 [doi]
• Learning-Based and Unrolled Motion-Compensated Reconstruction for Cardiac MR CINE ImagingJiaZhen Pan, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik. 686-696 [doi]
• Accelerated Pseudo 3D Dynamic Speech MR Imaging at 3T Using Unsupervised Deep Variational Manifold LearningRushdi Zahid Rusho, Qing Zou, Wahidul Alam, Subin Erattakulangara, Mathews Jacob, Sajan Goud Lingala. 697-706 [doi]
• FSE Compensated Motion Correction for MRI Using Data Driven MethodsBrett Levac, Sidharth Kumar, Sofia Kardonik, Jonathan I. Tamir. 707-716 [doi]
• Personalized dMRI Harmonization on Cortical SurfaceYihao Xia, Yonggang Shi. 717-725 [doi]
• A Projection-Based K-space Transformer Network for Undersampled Radial MRI Reconstruction with Limited Training SubjectsChang Gao, Shu-Fu Shih, J. Paul Finn, Xiaodong Zhong. 726-736 [doi]
• Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI ReconstructionBeliz Gunel, Arda Sahiner, Arjun D. Desai, Akshay S. Chaudhari, Shreyas Vasanawala, Mert Pilanci, John M. Pauly. 737-747 [doi]
• DDPNet: A Novel Dual-Domain Parallel Network for Low-Dose CT ReconstructionRongjun Ge, Yuting He, Cong Xia, Hailong Sun 0006, Yikun Zhang, Dianlin Hu, Sijie Chen, Yang Chen 0008, Shuo Li 0001, Daoqiang Zhang. 748-757 [doi]
• Mapping in Cycles: Dual-Domain PET-CT Synthesis Framework with Cycle-Consistent ConstraintsJiadong Zhang, Zhiming Cui, Caiwen Jiang, Jingyang Zhang, Fei Gao, Dinggang Shen. 758-767 [doi]
• Optimal MRI Undersampling Patterns for Pathology LocalizationArtem Razumov, Oleg Y. Rogov, Dmitry V. Dylov. 768-779 [doi]
• Sensor Geometry Generalization to Untrained Conditions in Quantitative Ultrasound ImagingSeokHwan Oh, Myeong-Gee Kim, Youngmin Kim, Guil Jung, Hyuksool Kwon, Hyeon-Min Bae. 780-789 [doi]
• A Transformer-Based Iterative Reconstruction Model for Sparse-View CT ReconstructionWenjun Xia, Ziyuan Yang, Qizheng Zhou, Zexin Lu, Zhongxian Wang, Yi Zhang. 790-800 [doi]