Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries : 6th International Workshop, BrainLes 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Revised Selected Papers, Part I / edited by Alessandro Crimi, Spyridon Bakas.

Format:

Book

Contributor:

Crimi, Alessandro, Editor.

Bakas, Spyridon, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 12658

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12658

Language:

English

Subjects (All):

Computer vision.

Machine learning.

Pattern recognition systems.

Bioinformatics.

Computer Vision.

Machine Learning.

Automated Pattern Recognition.

Computational and Systems Biology.

Local Subjects:

Computer Vision.

Machine Learning.

Automated Pattern Recognition.

Computational and Systems Biology.

Physical Description:

1 online resource (XX, 529 pages) : 197 illustrations, 180 illustrations in color.

Edition:

1st ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

This two-volume set LNCS 12658 and 12659 constitutes the thoroughly refereed proceedings of the 6th International MICCAI Brainlesion Workshop, BrainLes 2020, the International Multimodal Brain Tumor Segmentation (BraTS) challenge, and the Computational Precision Medicine: Radiology-Pathology Challenge on Brain Tumor Classification (CPM-RadPath) challenge. These were held jointly at the 23rd Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2020, in Lima, Peru, in October 2020.* The revised selected papers presented in these volumes were organized in the following topical sections: brain lesion image analysis (16 selected papers from 21 submissions); brain tumor image segmentation (69 selected papers from 75 submissions); and computational precision medicine: radiology-pathology challenge on brain tumor classification (6 selected papers from 6 submissions). *The workshop and challenges were held virtually.

Contents:

Invited Papers

Glioma Diagnosis and Classification: Illuminating the Gold Standard

Multiple Sclerosis Lesion Segmentation - A Survey of Supervised CNN-Based Methods

Computational Diagnostics of GBM Tumors in the Era of Radiomics and Radiogenomics

Brain Lesion Image Analysis

Automatic Segmentation of Non-Tumor Tissues in Glioma MR Brain Images Using Deformable Registration with Partial Convolutional Networks

Convolutional neural network with asymmetric encoding and decoding structure for brain vessel segmentation on computed tomographic angiography

Volume Preserving Brain Lesion Segmentation

Microstructural modulations in the hippocampus allow to characterizing relapsing-remitting versus primary progressive multiple sclerosis

Symmetric-Constrained Irregular Structure Inpainting for Brain MRI Registration with Tumor Pathology

Multivariate analysis is sufficient for lesion-behaviour mapping

Label-Efficient Multi-Task Segmentation using Contrastive Learning

Spatio-temporal Learning from Longitudinal Data for Multiple Sclerosis Lesion Segmentation

MMSSD: Multi-scale and Multi-level Single Shot Detector for Brain Metastases Detection

Unsupervised 3D Brain Anomaly Detection

Assessing Lesion Segmentation Bias of Neural Networks on Motion Corrupted Brain MRI Tejas Sudharshan Mathai, Yi Wang, Nathan Cross

Estimating Glioblastoma Biophysical Growth Parameters Using Deep Learning Regression

Bayesian Skip Net: Building on Prior Information for the Prediction and Segmentation of Stroke Lesions

Brain Tumor Segmentation

Brain Tumor Segmentation Using Dual-Path Attention U-net in 3D MRI Images

Multimodal Brain Image Analysis and Survival Prediction

Using Neuromorphic Attention-based Neural Networks

Context Aware 3D UNet for Brain Tumor Segmentation

Modality-Pairing Learning for Brain Tumor Segmentation

Transfer Learning for Brain Tumor Segmentation

Efficient embedding network for 3D brain tumor segmentation

Segmentation of the multimodal brain tumor images used Res-U-Net

Vox2Vox: 3D-GAN for Brain Tumour Segmentation

Automatic Brain Tumor Segmentation with Scale Attention Network

Impact of Spherical Coordinates Transformation Pre-processing in Deep Convolution Neural Networks for Brain Tumor Segmentation and Survival Prediction

Overall Survival Prediction for Glioblastoma on Pre-Treatment MRI Using Robust Radiomics and Priors

Glioma segmentation using encoder-decoder network and survival prediction based on cox analysis

Brain tumor segmentation with self-ensembled, deeply-supervised 3D U-net neural networks: a BraTS 2020 challenge solution

Brain tumour segmentation using a triplanar ensemble of U-Nets on MR images

MRI brain tumor segmentation using a 2D-3D U-Net ensemble

Multimodal Brain Tumor Segmentation and Survival Prediction Using a 3D Self-Ensemble ResUNet

MRI Brain Tumor Segmentation and Uncertainty Estimation using 3D-UNet architectures

Utility of Brain Parcellation in Enhancing Brain Tumor Segmentation and Survival Prediction

Uncertainty-driven refinement of tumor core segmentation using 3D-to-2D networks with label uncertainty

Multi-Decoder Networks with Multi-Denoising Inputs for Tumor Segmentation

MultiATTUNet: Brain Tumor Segmentation and Survival Multitasking

A Two-Stage Cascade Model with Variational Autoencoders and Attention Gates for MRI Brain Tumor Segmentation

Ensemble of Two Dimensional Networks for Bain Tumor Segmentation

Cascaded Coarse-to-Fine Neural Network for Brain Tumor Segmentation

Low-Rank Convolutional Networks for Brain Tumor Segmentation

Brain tumour segmentation using cascaded 3D densely-connected U-net

Segmentation then Prediction: A Multi-task Solution to Brain Tumor Segmentation and Survival Prediction

Enhancing MRI Brain Tumor Segmentation with an Additional Classification Network

Self-training for Brain Tumour Segmentation with Uncertainty Estimation and Biophysics-Guided Survival Prediction.

Other Format:

Printed edition:

ISBN:

978-3-030-72084-1

9783030720841

Access Restriction:

Restricted for use by site license.