Divide and Conquer: Stratifying Training Data by Tumor Grade Improves Deep Learning-Based Brain Tumor Segmentation-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Divide and Conquer: Stratifying Training Data by Tumor Grade Improves Deep Learning-Based Brain Tumor Segmentation

Published:2019-11-05 Issue: Volume:13 Page:
ISSN:1662-453X
Container-title:Frontiers in Neuroscience
language:
Short-container-title:Front. Neurosci.

Author:

Rebsamen Michael,Knecht Urspeter,Reyes Mauricio,Wiest Roland,Meier Raphael,McKinley Richard

Funder

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Krebsliga Schweiz

Publisher

Frontiers Media SA

Subject

General Neuroscience

Reference52 articles.

1. A modality-adaptive method for segmenting brain tumors and organs-at-risk in radiation therapy planning;Agn;Med. Image Anal.,2019

2. Assessment of the pathological grade of astrocytic gliomas using an MRI score;Asari;Neuroradiology,1994

3. Segmentation labels for the pre-operative scans of the TCGA-GBM collection;Bakas;The Cancer Imaging Archive

4. Segmentation labels for the pre-operative scans of the TCGA-LGG collection;Bakas;The Cancer Imaging Archive

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

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. GETNet: Group Normalization Shuffle and Enhanced Channel Self-Attention Network Based on VT-UNet for Brain Tumor Segmentation;Diagnostics;2024-06-14

2. Toward Improved Accuracy in Quasi-Static Elastography Using Deep Learning;Computer Modeling in Engineering & Sciences;2024

3. MimicNet: Mimicking manual delineation of human expert for brain tumor segmentation from multimodal MRIs;Applied Soft Computing;2023-08

4. Golgi-apparatus genes related signature for predicting the progression-free interval of patients with papillary thyroid carcinoma;BMC Medical Genomics;2023-03-27

5. Recent advancement in learning methodology for segmenting brain tumor from magnetic resonance imaging -a review;Multimedia Tools and Applications;2023-02-28

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3