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Medical Image Computing and Computer Assisted Intervention - MICCAI 2021
24th International Conference, Strasbourg, France, September 27-October 1, 2021, Proceedings, Part IV
1 online resource (XXXVII, 682 pages 8 illustrations)
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.
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.
edited by Marleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert.
Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12904