Medical Image Computing and Computer Assisted Intervention - MICCAI 2021
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Medical Image Computing and Computer Assisted Intervention - MICCAI 2021

Medical Image Computing and Computer Assisted Intervention - MICCAI 2021


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About the Book

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.-


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Product Details
  • ISBN-13: 9783030872014
  • Publisher: Springer Nature Switzerland AG
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Sub Title: 24th International Conference, Strasbourg, France, September 27-October 1, 2021, Proceedings, Part IV
  • Width: 156 mm
  • ISBN-10: 3030872017
  • Publisher Date: 23 Sep 2021
  • Height: 234 mm
  • No of Pages: 722
  • Spine Width: 37 mm
  • Weight: 1047 gr


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Medical Image Computing and Computer Assisted Intervention - MICCAI 2021
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