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Medical Image Computing and Computer Assisted Intervention – MICCAI 2022

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Medical Image Computing and Computer Assisted Intervention – MICCAI 2022
Springer Nature Switzerland

Table of Contents

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    Book Overview
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    Chapter 1 SVoRT: Iterative Transformer for Slice-to-Volume Registration in Fetal Brain MRI
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    Chapter 2 Double-Uncertainty Guided Spatial and Temporal Consistency Regularization Weighting for Learning-Based Abdominal Registration
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    Chapter 3 Unsupervised Deformable Image Registration with Absent Correspondences in Pre-operative and Post-recurrence Brain Tumor MRI Scans
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    Chapter 4 On the Dataset Quality Control for Image Registration Evaluation
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    Chapter 5 Dual-Branch Squeeze-Fusion-Excitation Module for Cross-Modality Registration of Cardiac SPECT and CT
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    Chapter 6 Embedding Gradient-Based Optimization in Image Registration Networks
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    Chapter 7 ContraReg: Contrastive Learning of Multi-modality Unsupervised Deformable Image Registration
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    Chapter 8 Swin-VoxelMorph: A Symmetric Unsupervised Learning Model for Deformable Medical Image Registration Using Swin Transformer
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    Chapter 9 Non-iterative Coarse-to-Fine Registration Based on Single-Pass Deep Cumulative Learning
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    Chapter 10 DSR: Direct Simultaneous Registration for Multiple 3D Images
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    Chapter 11 Multi-modal Retinal Image Registration Using a Keypoint-Based Vessel Structure Aligning Network
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    Chapter 12 A Deep-Discrete Learning Framework for Spherical Surface Registration
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    Chapter 13 Privacy Preserving Image Registration
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    Chapter 14 Deformer: Towards Displacement Field Learning for Unsupervised Medical Image Registration
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    Chapter 15 End-to-End Multi-Slice-to-Volume Concurrent Registration and Multimodal Generation
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    Chapter 16 Fast Spherical Mapping of Cortical Surface Meshes Using Deep Unsupervised Learning
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    Chapter 17 Learning-Based US-MR Liver Image Registration with Spatial Priors
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    Chapter 18 Unsupervised Deep Non-rigid Alignment by Low-Rank Loss and Multi-input Attention
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    Chapter 19 Transformer Lesion Tracker
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    Chapter 20 LiftReg: Limited Angle 2D/3D Deformable Registration
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    Chapter 21 XMorpher: Full Transformer for Deformable Medical Image Registration via Cross Attention
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    Chapter 22 Weakly-Supervised Biomechanically-Constrained CT/MRI Registration of the Spine
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    Chapter 23 Collaborative Quantization Embeddings for Intra-subject Prostate MR Image Registration
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    Chapter 24 Mesh-Based 3D Motion Tracking in Cardiac MRI Using Deep Learning
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    Chapter 25 Data-Driven Multi-modal Partial Medical Image Preregistration by Template Space Patch Mapping
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    Chapter 26 Global Multi-modal 2D/3D Registration via Local Descriptors Learning
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    Chapter 27 Adapting the Mean Teacher for Keypoint-Based Lung Registration Under Geometric Domain Shifts
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    Chapter 28 DisQ: Disentangling Quantitative MRI Mapping of the Heart
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    Chapter 29 Learning Iterative Optimisation for Deformable Image Registration of Lung CT with Recurrent Convolutional Networks
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    Chapter 30 Electron Microscope Image Registration Using Laplacian Sharpening Transformer U-Net
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    Chapter 31 Undersampled MRI Reconstruction with Side Information-Guided Normalisation
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    Chapter 32 Noise2SR: Learning to Denoise from Super-Resolved Single Noisy Fluorescence Image
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    Chapter 33 RPLHR-CT Dataset and Transformer Baseline for Volumetric Super-Resolution from CT Scans
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    Chapter 34 A Learnable Variational Model for Joint Multimodal MRI Reconstruction and Synthesis
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    Chapter 35 Autofocusing+: Noise-Resilient Motion Correction in Magnetic Resonance Imaging
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    Chapter 36 Tagged-MRI Sequence to Audio Synthesis via Self Residual Attention Guided Heterogeneous Translator
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    Chapter 37 Only-Train-Once MR Fingerprinting for Magnetization Transfer Contrast Quantification
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    Chapter 38 AutoGAN-Synthesizer: Neural Architecture Search for Cross-Modality MRI Synthesis
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    Chapter 39 Multi-scale Super-Resolution Magnetic Resonance Spectroscopic Imaging with Adjustable Sharpness
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    Chapter 40 Progressive Subsampling for Oversampled Data - Application to Quantitative MRI
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    Chapter 41 Deep-Learning Based T 1 and T 2 Quantification from Undersampled Magnetic Resonance Fingerprinting Data to Track Tracer Kinetics in Small Laboratory Animals
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    Chapter 42 NAF: Neural Attenuation Fields for Sparse-View CBCT Reconstruction
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    Chapter 43 UASSR: Unsupervised Arbitrary Scale Super-Resolution Reconstruction of Single Anisotropic 3D Images via Disentangled Representation Learning
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    Chapter 44 WavTrans: Synergizing Wavelet and Cross-Attention Transformer for Multi-contrast MRI Super-Resolution
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    Chapter 45 DuDoCAF: Dual-Domain Cross-Attention Fusion with Recurrent Transformer for Fast Multi-contrast MR Imaging
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    Chapter 46 Weakly Supervised MR-TRUS Image Synthesis for Brachytherapy of Prostate Cancer
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    Chapter 47 Domain-Adaptive 3D Medical Image Synthesis: An Efficient Unsupervised Approach
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    Chapter 48 What Can We Learn About a Generated Image Corrupting Its Latent Representation?
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    Chapter 49 3D CVT-GAN: A 3D Convolutional Vision Transformer-GAN for PET Reconstruction
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    Chapter 50 Classification-Aided High-Quality PET Image Synthesis via Bidirectional Contrastive GAN with Shared Information Maximization
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    Chapter 51 Swin Deformable Attention U-Net Transformer (SDAUT) for Explainable Fast MRI
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    Chapter 52 Low-Dose CT Reconstruction via Dual-Domain Learning and Controllable Modulation
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    Chapter 53 Graph-Based Compression of Incomplete 3D Photoacoustic Data
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    Chapter 54 DS $$^3$$ 3 -Net: Difficulty-Perceived Common-to-T1ce Semi-supervised Multimodal MRI Synthesis Network
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    Chapter 55 Invertible Sharpening Network for MRI Reconstruction Enhancement
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    Chapter 56 Analyzing and Improving Low Dose CT Denoising Network via HU Level Slicing
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    Chapter 57 Spatio-Temporal Motion Correction and Iterative Reconstruction of In-Utero Fetal fMRI
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    Chapter 58 Deep Filter Bank Regression for Super-Resolution of Anisotropic MR Brain Images
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    Chapter 59 Towards Performant and Reliable Undersampled MR Reconstruction via Diffusion Model Sampling
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    Chapter 60 Patch-Wise Deep Metric Learning for Unsupervised Low-Dose CT Denoising
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    Chapter 61 BMD-GAN: Bone Mineral Density Estimation Using X-Ray Image Decomposition into Projections of Bone-Segmented Quantitative Computed Tomography Using Hierarchical Learning
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    Chapter 62 Measurement-Conditioned Denoising Diffusion Probabilistic Model for Under-Sampled Medical Image Reconstruction
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    Chapter 63 Orientation-Shared Convolution Representation for CT Metal Artifact Learning
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    Chapter 64 MRI Reconstruction by Completing Under-sampled K-space Data with Learnable Fourier Interpolation
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    Chapter 65 Learning-Based and Unrolled Motion-Compensated Reconstruction for Cardiac MR CINE Imaging
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    Chapter 66 Accelerated Pseudo 3D Dynamic Speech MR Imaging at 3T Using Unsupervised Deep Variational Manifold Learning
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    Chapter 67 FSE Compensated Motion Correction for MRI Using Data Driven Methods
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    Chapter 68 Personalized dMRI Harmonization on Cortical Surface
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    Chapter 69 A Projection-Based K-space Transformer Network for Undersampled Radial MRI Reconstruction with Limited Training Subjects
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    Chapter 70 Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI Reconstruction
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    Chapter 71 DDPNet: A Novel Dual-Domain Parallel Network for Low-Dose CT Reconstruction
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    Chapter 72 Mapping in Cycles: Dual-Domain PET-CT Synthesis Framework with Cycle-Consistent Constraints
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    Chapter 73 Optimal MRI Undersampling Patterns for Pathology Localization
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    Chapter 74 Sensor Geometry Generalization to Untrained Conditions in Quantitative Ultrasound Imaging
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    Chapter 75 A Transformer-Based Iterative Reconstruction Model for Sparse-View CT Reconstruction
Attention for Chapter 9: Non-iterative Coarse-to-Fine Registration Based on Single-Pass Deep Cumulative Learning
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Summary
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Chapter title
Non-iterative Coarse-to-Fine Registration Based on Single-Pass Deep Cumulative Learning
Chapter number 9
Book title
Medical Image Computing and Computer Assisted Intervention – MICCAI 2022
Published by
Springer, Cham, January 2022
DOI 10.1007/978-3-031-16446-0_9
Book ISBNs
978-3-03-116445-3, 978-3-03-116446-0
Authors

Meng, Mingyuan, Bi, Lei, Feng, Dagan, Kim, Jinman

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 15%
Student > Master 2 15%
Lecturer 1 8%
Unspecified 1 8%
Unknown 7 54%
Readers by discipline Count As %
Computer Science 3 23%
Engineering 2 15%
Unspecified 1 8%
Unknown 7 54%

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