A new method for skull stripping in brain MRI using multistable cellular neural networks
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
http://link.springer.com/article/10.1007/s00521-016-2834-2/fulltext.html
Reference40 articles.
1. Somasundaram K, Kalaiselvi T (2011) Automatic brain extraction methods for T1 magnetic resonance images using region labeling and morphological operations. Comput Biol Med 41:716–725
2. El-Dahshan E-SA, Mohsen HM, Revett K, Salem A-BM (2014) Computer-aided diagnosis of human brain tumor through MRI: a survey and a new algorithm. Expert Syst Appl 41:5526–5545
3. Demirhan A, Güler İ (2011) Combining stationary wavelet transform and self-organizing maps for brain MR image segmentation. Eng Appl Artif Intell 24:358–367
4. Tanoori B, Azimifar Z, Shakibafar A, Katebi S (2011) Brain volumetry: an active contour model-based segmentation followed by SVM-based classification. Comput Biol Med 41:619–632
5. Rajendran A, Dhanasekaran R (2012) Fuzzy clustering and deformable model for tumor segmentation on MRI brain image: a combined approach. Proced Eng 30:327–333
Cited by 13 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. A new clinical diagnosis system for detecting brain tumor using integrated ResNet_Stacking with XGBoost;Biomedical Signal Processing and Control;2024-10
2. Fully Automated Skull Stripping from Brain Magnetic Resonance Images Using Mask RCNN-Based Deep Learning Neural Networks;Brain Sciences;2023-08-28
3. Automatic skull prototyping framework for damage detection and repairing using computer vision and deep learning techniques;International Journal of Information Technology;2022-05-19
4. A comparative study and overview on the magnetic resonance images skull stripping methods and their correspondence techniques;INT J NONLINEAR ANAL;2022
5. Brain Tumor Detection Using Machine Learning and Deep Learning: A Review;Current Medical Imaging Formerly Current Medical Imaging Reviews;2021-09-23
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