Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 24th International Conference, Strasbourg, France, September 27-October 1, 2021, Proceedings, Part IV

• Main Authors: de Bruijne, Marleen, Cattin, Philippe C, Cotin, Stéphane, Padoy, Nicolas, Speidel, Stefanie, Zheng, Yefeng, Essert, Caroline
• Format: eBook
• Language: English
• Published: Cham Springer International Publishing AG 2021; Springer International Publishing
• Edition: 1
• Series: Lecture Notes in Computer Science
• Subjects: Diagnostic imaging-Data processing-Congresses
• ISBN: 9783030872014; 3030872017

The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.* The 531 r...

Table of Contents:

• 3 Experiments and Results -- 3.1 Implementation Details -- 3.2 Validation of Registration -- 3.3 Validation of Internal Probabilistic Deformation Model -- 4 Discussion and Conclusion -- References -- Learning Dual Transformer Network for Diffeomorphic Registration -- 1 Introduction -- 2 Proposed Method -- 2.1 Volumetric Image Embedding -- 2.2 Dual Transformer -- 2.3 Diffeomorphic Registration -- 2.4 Unsupervised Learning -- 3 Experiments -- 3.1 Qualitative Assessment -- 4 Conclusion -- References -- Construction of Longitudinally Consistent 4D Infant Cerebellum Atlases Based on Deep Learning -- 1 Introduction -- 2 Method -- 2.1 Deformable Atlas Construction Network (DACN) -- 2.2 Affine Atlas Rescaling Network (AARN) -- 3 Experiments -- 4 Conclusion -- References -- Nesterov Accelerated ADMM for Fast Diffeomorphic Image Registration -- 1 Introduction -- 2 Diffeomorphic Image Registration -- 3 Nesterov Accelerated ADMM -- 4 Experimental Results -- 5 Conclusion -- References -- Spectral Embedding Approximation and Descriptor Learning for Craniofacial Volumetric Image Correspondence -- 1 Introduction -- 2 Method -- 2.1 Volumetric Image Descriptor -- 2.2 Spectral Embedding Approximation -- 2.3 Spectral Map-Based Correspondence -- 3 Experiments -- 3.1 Qualitative Assessment -- 4 Conclusion -- References -- A Deep Network for Joint Registration and Parcellation of Cortical Surfaces -- 1 Introduction -- 2 Method -- 2.1 Network Architecture -- 2.2 Loss Functions -- 2.3 Training Strategy -- 3 Experiments and Results -- 3.1 Experimental Setting -- 3.2 Results -- 4 Conclusion -- References -- 4D-Foot: A Fully Automated Pipeline of Four-Dimensional Analysis of the Foot Bones Using Bi-plane X-Ray Video and CT -- 1 Introduction -- 2 Method -- 2.1 Overview of the Proposed Pipeline -- 2.2 Automated Segmentation and Landmark Detection
• Adversarial Domain Feature Adaptation for Bronchoscopic Depth Estimation
• Multimodal Sensing Guidewire for C-Arm Navigation with Random UV Enhanced Optical Sensors Using Spatio-Temporal Networks -- 1 Introduction -- 2 Materials and Methods -- 2.1 Device Fabrication with UV Enhanced Random Gratings -- 2.2 Event Trajectory Generation of Wavelength Data -- 2.3 Shape and Flow Networks -- 2.4 Refinement Network -- 2.5 Implementation Details -- 3 Results -- 3.1 Experimental Setup and Training Data -- 3.2 Synthetic and In-Vivo Experiments -- 4 Conclusion -- References -- Image-to-Graph Convolutional Network for Deformable Shape Reconstruction from a Single Projection Image -- 1 Introduction -- 2 Methods -- 2.1 Dataset and Problem Definition -- 2.2 Image-to-Graph Convolutional Network -- 2.3 Loss Functions -- 3 Experiments -- 4 Conclusion -- References -- Class-Incremental Domain Adaptation with Smoothing and Calibration for Surgical Report Generation -- 1 Introduction -- 2 Proposed Method -- 2.1 Preliminaries -- 2.2 Feature Extraction -- 2.3 Captioning Model -- 3 Experiments -- 3.1 Dataset -- 3.2 Implementation Details -- 4 Results and Evaluation -- 5 Discussion and Conclusion -- References -- Real-Time Rotated Convolutional Descriptor for Surgical Environments -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 Network Structure -- 3.2 Matching -- 3.3 Model Training -- 4 Experiments -- 4.1 Model Accuracy -- 4.2 Model Speed -- 5 Conclusion -- References -- Surgical Instruction Generation with Transformers -- 1 Introduction -- 2 Methodology -- 2.1 Encoder-Decoder with Transformer Backbone -- 2.2 Reinforcement Learning -- 3 Evaluation -- 3.1 Experimental Settings -- 3.2 Implementation and Training Details -- 4 Results and Discussion -- 4.1 Comparison with the State-of-the-Art -- 4.2 Effects of Reinforcement Learning -- 4.3 Limitations and Challenges -- 5 Conclusion -- References
• Intro -- Preface -- Organization -- Contents - Part IV -- Image Registration -- Medical Image Registration Based on Uncoupled Learning and Accumulative Enhancement -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Uncoupled Spatial Encoder -- 2.3 Accumulative Warping Enhancement -- 2.4 Multi-window Loss -- 3 Experiments and Results -- 4 Conclusion -- References -- Atlas-based Segmentation of Intracochlear Anatomy in Metal Artifact Affected CT Images of the Ear with Co-trained Deep Neural Networks -- 1 Introduction -- 2 Method -- 2.1 Data -- 2.2 Learning to Register the Artifact-Affected Images and the Atlas Image with Assistance of the Paired Artifact-Free Images -- 2.3 Network Architecture -- 2.4 Evaluation -- 3 Experiments -- 4 Results -- 5 Summary -- References -- Learning Unsupervised Parameter-Specific Affine Transformation for Medical Images Registration*-8pt -- 1 Introduction -- 2 Methods -- 2.1 Parameter-Specific Affine Transformation -- 2.2 Cross-stitch Affine Network -- 3 Experiments and Results -- 4 Conclusion -- References -- Conditional Deformable Image Registration with Convolutional Neural Network -- 1 Introduction -- 2 Methods -- 2.1 Conditional Deformable Image Registration -- 2.2 Conditional Image Registration Module -- 2.3 Self-supervised Learning -- 3 Experiments -- 4 Conclusion -- References -- A Deep Discontinuity-Preserving Image Registration Network -- 1 Introduction -- 2 Method -- 3 Experiments and Results -- 4 Conclusion -- References -- End-to-end Ultrasound Frame to Volume Registration -- 1 Introduction -- 2 Problem Definition -- 3 Method -- 3.1 End-to-end Slice-to-Volume Registration -- 3.2 Implementation Details -- 4 Experiments and Results -- 4.1 Datasets and Experimental Setting -- 4.2 Results Evaluation -- 5 Conclusions -- References -- Cross-Modal Attention for MRI and Ultrasound Volume Registration
• 2.3 2D-3D Registration Incorporating Landmark Reprojection Error -- 3 Experiment and Results -- 3.1 Experimental Materials -- 3.2 Evaluation of Automated Segmentation and Landmark Detection -- 3.3 Evaluation of 2D-3D Registration Using Bone Phantom -- 3.4 Evaluation of 2D-3D Registration Using Images of Real Subjects -- 4 Discussion and Conclusion -- References -- Equivariant Filters for Efficient Tracking in 3D Imaging -- 1 Introduction -- 1.1 Previous Work -- 2 Method -- 2.1 Construction of Equivariant Convolutional Filters -- 2.2 Registration of Equivaritant Filters -- 2.3 Loss Functions and Implementations -- 3 Experiments -- 4 Discussion and Conclusion -- References -- Revisiting Iterative Highly Efficient Optimisation Schemes in Medical Image Registration -- 1 Introduction/Motivation -- 2 Method -- 3 Experiments -- 3.1 Datasets -- 4 Results -- 5 Discussion and Conclusion -- References -- Multi-scale Neural ODEs for 3D Medical Image Registration -- 1 Introduction -- 2 Method -- 2.1 Learn Registration Optimizer via Neural ODEs -- 2.2 Pretrained Feature Extraction Network -- 3 Experiments and Results -- 3.1 Experiment Setup -- 3.2 Results -- 4 Discussions and Conclusions -- References -- Image-Guided Interventions and Surgery -- Self-supervised Generative Adversarial Network for Depth Estimation in Laparoscopic Images -- 1 Introduction -- 2 Methodology -- 2.1 Overview -- 2.2 Network Architecture -- 2.3 Training Losses -- 3 Experiments and Results -- 3.1 Dataset -- 3.2 Evaluation Metrics, Baseline, and Implementation Details -- 3.3 Results -- 4 Conclusions -- References -- Personalized Respiratory Motion Model Using Conditional Generative Networks for MR-Guided Radiotherapy -- 1 Introduction -- 2 Methods -- 2.1 Model Building -- 2.2 Model Personalization and Application -- 3 Experimental Setup and Results -- 4 Conclusion -- References
• 1 Introduction -- 2 Method -- 2.1 Cross-Modal Attention -- 2.2 Feature Extraction and Deep Registration Modules -- 2.3 Implementation Details -- 3 Experiments and Results -- 3.1 Dataset and Preprocessing -- 3.2 Experimental Results -- 4 Conclusion -- References -- Bayesian Atlas Building with Hierarchical Priors for Subject-Specific Regularization -- 1 Introduction -- 2 Background: Atlas Building with Fast LDDMM -- 3 Our Model: Bayesian Atlas Building with Hierarchical Priors -- 3.1 Model Inference -- 4 Experimental Evaluation -- 5 Conclusion -- References -- SAME: Deformable Image Registration Based on Self-supervised Anatomical Embeddings -- 1 Introduction -- 2 Method -- 2.1 Self-supervised Anatomical Embedding (SAM) -- 2.2 SAM-Affine and SAM-Coarse -- 2.3 SAM-VoxelMorph -- 3 Experiments -- 4 Conclusion -- References -- Weakly Supervised Registration of Prostate MRI and Histopathology Images -- 1 Introduction -- 2 Methods -- 2.1 Data Acquisition -- 2.2 Overview of Proposed Method -- 2.3 Registration Neural Network -- 2.4 Transformation Model -- 2.5 Loss Functions -- 2.6 Previous Method -- 2.7 Evaluation Metrics -- 2.8 Experimental Design -- 3 Results -- 3.1 Qualitative Results -- 3.2 Quantitative Results -- 4 Discussion and Conclusion -- References -- 4D-CBCT Registration with a FBCT-derived Plug-and-Play Feasibility Regularizer -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Feasibility Descriptor of Respiratory Motion -- 2.3 Unsupervised Learning for DVF Estimation -- 3 Experiments and Results -- 3.1 Training of the Feasibility Descriptor -- 3.2 Training of the DVF Inference Network -- 3.3 Evaluation -- 3.4 Results -- 4 Discussion and Conclusion -- References -- Unsupervised Diffeomorphic Surface Registration and Non-linear Modelling -- 1 Introduction -- 2 Methods -- 2.1 Registration Model -- 2.2 CVAE Network -- 2.3 Objective Function