Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 [E-Book] : 24th International Conference, Strasbourg, France, September 27-October 1, 2021, Proceedings, Part I / edited by Marleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert.
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 542 r...
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Personal Name(s): | Cattin, Philippe C., editor |
Cotin, Stéphane, editor / Essert, Caroline, editor / Padoy, Nicolas, editor / Speidel, Stefanie, editor / Zheng, Yefeng, editor / de Bruijne, Marleen, editor | |
Edition: |
1st edition 2021. |
Imprint: |
Cham :
Springer,
2021
|
Physical Description: |
XXXVII, 746 pages 252 illustrations (online resource) |
Note: |
englisch |
ISBN: |
9783030871932 |
DOI: |
10.1007/978-3-030-87193-2 |
Series Title: |
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"name" and "number" keys or a flat string containing only the series
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Image Processing, Computer Vision, Pattern Recognition, and Graphics ;
12901 /* Depending on the record driver, $field may either be an array with "name" and "number" keys or a flat string containing only the series name. We should account for both cases to maximize compatibility. */?> Lecture Notes in Computer Science |
Subject (LOC): |
- Image Segmentation
- Noisy Labels are Treasure: Mean-Teacher-Assisted Confident Learning for Hepatic Vessel Segmentation
- TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation
- Pancreas CT Segmentation by Predictive Phenotyping
- Medical Transformer: Gated Axial-Attention for Medical Image Segmentation
- Anatomy-Constrained Contrastive Learning for Synthetic Segmentation without Ground-truth
- Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy Labels
- Multi-phase Liver Tumor Segmentation with Spatial Aggregation and Uncertain Region Inpainting
- Convolution-Free Medical Image Segmentation using Transformer Networks
- Consistent Segmentation of Longitudinal Brain MR Images with Spatio-Temporal Constrained Networks
- A Multi-Branch Hybrid Transformer Network for Corneal Endothelial Cell Segmentation
- TransBTS: Multimodal Brain Tumor Segmentation Using Transformer
- Automatic Polyp Segmentation via Multi-scale Subtraction Network
- Patch-Free 3D Medical Image Segmentation Driven by Super-Resolution Technique and Self-Supervised Guidance
- Progressively Normalized Self-Attention Network for Video Polyp Segmentation
- SGNet: Structure-aware Graph-based Network for Airway Semantic Segmentation
- NucMM Dataset: 3D Neuronal Nuclei Instance Segmentation at Sub-Cubic Millimeter Scale
- AxonEM Dataset: 3D Axon Instance Segmentation of Brain Cortical Regions
- Improved Brain Lesion Segmentation with Anatomical Priors from Healthy Subjects
- CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation
- Boundary-aware Transformers for Skin Lesion Segmentation
- A Topological-Attention ConvLSTM Network and Its Application to EM Images
- BiX-NAS: Searching Efficient Bi-directional Architecture for Medical Image Segmentation
- Multi-Task, Multi-Domain Deep Segmentation with Shared Representations and Contrastive Regularization for Sparse Pediatric Datasets
- TEDS-Net: Enforcing Diffeomorphisms in Spatial Transformers to Guarantee Topology Preservation in Segmentations
- Learning Consistency- and Discrepancy-Context for 2D Organ Segmentation
- Partial-supervised Learning for Vessel Segmentation in Ocular Images
- Unsupervised Network Learning for Cell Segmentation
- MT-UDA: Towards Unsupervised Cross-Modality Medical Image Segmentation with Limited Source Labels
- Context-aware virtual adversarial training for anatomically-plausible segmentation
- Interactive segmentation via deep learning and B-spline explicit active surfaces
- Multi-Compound Transformer for Accurate Biomedical Image Segmentation
- kCBAC-Net: Deeply Supervised Complete Bipartite Networks with Asymmetric Convolutions for Medical Image Segmentation
- Multi-frame Attention Network for Left Ventricle Segmentation in 3D Echocardiography
- Coarse-to-fine Segmentation of Organs at Risk in Nasopharyngeal Carcinoma Radiotherapy
- Joint Segmentation and Quantification of Main Coronary Vessels Using Dual-branch Multi-scale Attention Network
- A Spatial Guided Self-supervised Clustering Network for Medical Image Segmentation
- Comprehensive Importance-based Selective Regularization for Continual Segmentation Across Multiple Sites
- ReSGAN: Intracranial Hemorrhage Segmentation with Residuals of Synthetic Brain CT Scans
- Refined Local-imbalance-based Weight for Airway Segmentation in CT
- Selective Learning from External Data for CT Image Segmentation
- Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT
- MouseGAN: GAN-Based Multiple MRI Modalities Synthesis and Segmentation for Mouse Brain Structures
- Style Curriculum Learning for Robust Medical Image Segmentation
- Towards Efficient Human-Machine Collaboration: Real-Time Correction Effort Prediction for Ultrasound Data Acquisition
- Residual Feedback Network for Breast Lesion Segmentation in Ultrasound Image
- Learning to Address Intra-segment Misclassification in Retinal Imaging
- Flip Learning: Erase to Segment
- DC-Net: Dual Context Network for 2D Medical Image Segmentation
- LIFE: A Generalizable Autodidactic Pipeline for 3D OCT-A Vessel Segmentation
- Superpixel-guided Iterative Learning from Noisy Labels for Medical Image Segmentation
- A hybrid attention ensemble framework for zonal prostate segmentation
- 3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation
- HRENet: A Hard Region Enhancement Network for Polyp Segmentation
- A Novel Hybrid Convolutional Neural Network for Accurate Organ Segmentation in 3D Head and Neck CT Images
- TumorCP: A Simple but Effective Object-Level Data Augmentation for Tumor Segmentation
- Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation
- Hybrid graph convolutional neural networks for anatomical segmentation
- RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT Scans
- Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation
- CCBANet: Cascading Context and Balancing Attention for Polyp Segmentation
- Point-Unet: A Context-aware Point-based Neural Network for Volumetric Segmentation
- TUN-Det: A Novel Network for Thyroid Ultrasound Nodule Detection
- Distilling effective supervision for robust medical image segmentation with noisy labels
- On the relationship between calibrated predictors and unbiased volume estimation
- High-resolution segmentation of lumbar vertebrae from conventional thick slice MRI
- Shallow Attention Network for Polyp Segmentation
- A Line to Align: Deep Dynamic Time Warping for Retinal OCT Segmentation
- Learnable Oriented-Derivative Network for Polyp Segmentation
- LambdaUNet: 2.5D Stroke Lesion Segmentation of Diffusion-weighted MR Images.