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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 74: Sensor Geometry Generalization to Untrained Conditions in Quantitative Ultrasound Imaging
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Chapter title
Sensor Geometry Generalization to Untrained Conditions in Quantitative Ultrasound Imaging
Chapter number 74
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_74
Book ISBNs
978-3-03-116445-3, 978-3-03-116446-0
Authors

Oh, SeokHwan, Kim, Myeong-Gee, Kim, Youngmin, Jung, Guil, Kwon, Hyuksool, Bae, Hyeon-Min

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Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 33%
Student > Ph. D. Student 1 33%
Unknown 1 33%
Readers by discipline Count As %
Unspecified 1 33%
Computer Science 1 33%
Unknown 1 33%

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