Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 [electronic resource] : 24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part IV /

Image Registration -- Medical Image Registration Based on Uncoupled Learning and Accumulative Enhancement -- Atlas-Based Segmentation of Intracochlear Anatomy in Metal Artifact Affected CT Images of the Ear with Co-trained Deep Neural Networks -- Learning Unsupervised Parameter-specific Affine Transformation for Medical Images Registration -- Conditional Deformable Image Registration with Convolutional Neural Network -- A Deep Discontinuity-Preserving Image Registration Network -- End-to-end Ultrasound Frame to Volume Registration -- Cross-modal Attention for MRI and Ultrasound Volume Registration -- Bayesian Atlas Building with Hierarchical Priors for Subject-specific Regularization -- SAME: Deformable Image Registration based on Self-supervised Anatomical Embeddings -- Weakly Supervised Registration of Prostate MRI and Histopathology Images -- 4D-CBCT Registration with a FBCT-derived Plug-and-Play Feasibility Regularizer -- Unsupervised Diffeomorphic Surface Registration and Non-Linear Modelling -- Learning Dual Transformer Network for Diffeomorphic Registration -- Construction of Longitudinally Consistent 4D Infant Cerebellum Atlases based on Deep Learning -- Nesterov Accelerated ADMM for Fast Diffeomorphic Image Registration -- Spectral Embedding Approximation and Descriptor Learning for Craniofacial Volumetric Image Correspondence -- A Deep Network for Joint Registration and Parcellation of Cortical Surfaces -- 4D-Foot: A fully automated pipeline of four-dimensional analysis of the foot bones using bi-plane X-ray video and CT -- Equivariant Filters for Efficient Tracking in 3D Imaging -- Revisiting iterative highly efficient optimisation schemes in medical image registration -- Multi-scale Neural ODEs for 3D Medical Image Registration -- Image-Guided Interventions and Surgery -- Self-Supervised Generative Adversarial Network for Depth Estimation in Laparoscopic Images -- Personalized Respiratory Motion Model Using Conditional Generative Networks for MR-Guided Radiotherapy -- Multimodal Sensing Guidewire for C-arm Navigation with Random UV Enhanced Optical Sensors using Spatio-temporal Networks -- Image-to-Graph Convolutional Network for Deformable Shape Reconstruction from a Single Projection Image -- Class-Incremental Domain Adaptation with Smoothing and Calibration for Surgical Report Generation -- Real-Time Rotated Convolutional Descriptor for Surgical Environments -- Surgical Instruction Generation with Transformers -- Adversarial Domain Feature Adaptation for Bronchoscopic Depth Estimation -- 2.5D Thermometry Maps for MRI-guided Tumor Ablation -- Detection of critical structures in laparoscopic cholecystectomy using label relaxation and self-supervision -- EMDQ-SLAM: Real-time High-resolution Reconstruction of Soft Tissue Surface from Stereo Laparoscopy Videos -- Efficient Global-Local Memory for Real-time Instrument Segmentation of Robotic Surgical Video -- C-arm positioning for spinal standard projections in different intra-operative settings -- Quantitative Assessments for Ultrasound Probe Calibration -- Intra-operative Update of Boundary Conditions for Patient-specific Surgical Simulation -- Deep Iterative 2D/3D Registration -- hSDB-instrument: Instrument Localization Database for Laparoscopic and Robotic Surgeries -- Co-Generation and Segmentation for Generalized Surgical Instrument Segmentation on Unlabelled Data -- Surgical Data Science -- E-DSSR: Efficient Dynamic Surgical Scene Reconstruction with Transformer-based Stereoscopic Depth Perception -- CataNet: Predicting remaining cataract surgery duration -- Task Fingerprinting for Meta Learning in Biomedical Image Analysis -- Acoustic-based Spatio-temporal Learning for Press-fit Evaluation of Femoral Stem Implants -- Surgical Planning and Simulation -- Deep Simulation of Facial Appearance Changes Following Craniomaxillofacial Bony Movements in Orthognathic Surgical Planning -- A self-supervised deep framework for reference bony shape estimation in orthognathic surgical planning.-DLLNet: An Attention-based Deep Learning Method for Dental Landmark Localization on High-Resolution 3D Digital Dental Models -- Personalized CT Organ Dose Estimation from Scout Images -- High-particle simulation of Monte-Carlo dose distribution with 3D ConvLSTMs -- Effective semantic segmentation in Cataract surgery: What matters most? -- Facial and cochlear nerves characterization using deep reinforcement learning for landmark detection -- Patient-specific virtual spine straightening and vertebra inpainting: An automatic framework for osteoplasty planning -- A new Approach to Orthopedic Surgery Planning using Deep Reinforcement Learning and Simulation -- Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations -- Automatic Path Planning for Safe Guide Pin Insertion in PCL Reconstruction Surgery -- Improving hexahedral-FEM-based plasticity in surgery simulation -- Rapid treatment planning for low-dose-rate prostate brachytherapy with TP-GAN -- Surgical Skill and Work Flow Analysis -- Trans-SVNet: Accurate Phase Recognition from Surgical Videos via Hybrid Embedding Aggregation Transformer -- OperA: Attention-Regularized Transformers for Surgical Phase Recognition -- Surgical Workflow Anticipation using Instrument Interaction -- Multi-View Surgical Video Action Detection via Mixed Global View Attention -- Interhemispheric functional connectivity in the primary motor cortex distinguishes between training on a physical and a virtual surgical simulator -- Surgical Visualization and Mixed, Augmented and Virtual Reality -- Image-based Incision Detection for Topological Intraoperative 3D Model Update in Augmented Reality Assisted Laparoscopic Surgery -- Using Multiple Images and Contours for Deformable 3D-2D Registration of a Preoperative CT in Laparoscopic Liver Surgery -- SurgeonAssist-Net: Towards Context-Aware Head-Mounted Display-Based Augmented Reality for Surgical Guidance.

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 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging – others; and clinical applications - oncology Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound *The conference was held virtually.