Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries : : 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I / / edited by Alessandro Crimi, Spyridon Bakas.

• Superior document: Lecture Notes in Computer Science, 12962
• HerausgeberIn: Crimi, Alessandro.; Bakas, Spyridon.
• Place / Publishing House: Cham : : Springer International Publishing :, Imprint: Springer,, 2022.
• Year of Publication: 2022
• Edition: 1st ed. 2022.
• Language: English
• Series: Lecture Notes in Computer Science, 12962
• Physical Description: 1 online resource (XXI, 489 p. 171 illus., 134 illus. in color.)

This two-volume set LNCS 12962 and 12963 constitutes the thoroughly refereed proceedings of the 7th International MICCAI Brainlesion Workshop, BrainLes 2021, as well as the RSNA-ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge, the Federated Tumor Segmentation (FeTS) Challenge, the Cross-Modal...

Table of Contents

• Supervoxel Merging towards Brain Tumor Segmentation
• Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRI
• Modeling multi-annotator uncertainty as multi-class segmentation problem
• Modeling multi-annotator uncertainty as multi-class segmentation problem
• Adaptive unsupervised learning with enhanced feature representation for intra-tumor partitioning and survival prediction for glioblastoma
• Predicting isocitrate dehydrogenase mutation status in glioma using structural brain networks and graph neural networks
• Optimization of Deep Learning based Brain Extraction in MRI for Low Resource Environments. Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task
• Unet3D with Multiple Atrous Convolutions Attention Block for Brain Tumor Segmentation
• BRATS2021: exploring each sequence in multi-modal input for baseline U-net performance
• Automatic Brain Tumor Segmentation using Multi-scale Features and Attention Mechanism
• Simple and Fast Convolutional Neural Network applied to median cross sections for predicting the presence of MGMT promoter methylation in FLAIR MRI scans
• MSViT: Multi Scale Vision Transformer forBiomedical Image Segmentation
• Unsupervised Multimodal
• HarDNet-BTS: A Harmonic Shortcut Network for Brain Tumor Segmentation
• Multimodal Brain Tumor Segmentation Algorithm
• Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images
• Multi-plane UNet++ Ensemble for Glioblastoma Segmentation
• Multimodal Brain Tumor Segmentation using Modified UNet Architecture
• A video data based transfer learning approach for classification of MGMT status in brain tumor MR images
• Multimodal Brain Tumor Segmentation Using a 3D ResUNet in BraTS 2021
• 3D MRI brain tumour segmentation with autoencoder regularization and Hausdorff distance loss function
• 3D CMM-Net with Deeper Encoder for Semantic Segmentation of Brain Tumors in BraTS2021 Challenge
• Cascaded training pipeline for 3D brain tumor segmentation
• nnU-Net with Region-based Training and Loss Ensembles for Brain Tumor Segmentation
• Brain Tumor Segmentation Using Attention Activated U-Net with Positive Mining
• Automatic segmentation of brain tumor using 3D convolutional neural networks
• Hierarchical and Global Modality Interaction for Brain Tumor Segmentation
• Ensemble Outperforms Single Models in Brain Tumor Segmentation
• Brain Tumor Segmentation using UNet-Context Encoding Network
• Ensemble CNN Networks for GBM Tumors Segmentation using Multi-parametric MRI.