Brain Tumor Segmentation and Survival Prediction Using Multimodal MRI Scans With Deep Learning-Reference-Cited by-同舟云学术

Brain Tumor Segmentation and Survival Prediction Using Multimodal MRI Scans With Deep Learning

Published:2019-08-16 Issue: Volume:13 Page:
ISSN:1662-453X
Container-title:Frontiers in Neuroscience
language:
Short-container-title:Front. Neurosci.

Author:

Sun Li,Zhang Songtao,Chen Hang,Luo Lin

Funder

Shenzhen Science and Technology Innovation Commission

Publisher

Frontiers Media SA

Subject

General Neuroscience

Reference30 articles.

1. Segmentation labels and radiomic features for the pre-operative scans of the tcga-gbm collection;Bakas;Cancer Imaging Arch.

2. Segmentation labels and radiomic features for the pre-operative scans of the tcga-lgg collection;Bakas;Cancer Imaging Arch.

3. Advancing the cancer genome atlas glioma mri collections with expert segmentation labels and radiomic features;Bakas;Sci. Data

4. Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge;Bakas,2018

5. Recent advances in the molecular understanding of glioblastoma;Bleeker;J. Neuro Oncol.,2012

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