Brain Disease Diagnosis Using Deep Learning Features from Longitudinal MR Images
Author:
Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-96890-2_27
Reference24 articles.
1. Liu, S., Liu, S., Cai, W., Pujol, S., Kikinis, R., Feng, D.: Early diagnosis of Alzheimer’s disease with deep learning. In: ISBI, pp. 1015–1018. IEEE (2014)
2. Shi, J., Zheng, X., Li, Y., Zhang, Q., Ying, S.: Multimodal neuroimaging feature learning with multimodal stacked deep polynomial networks for diagnosis of Alzheimer’s disease. IEEE J. Biomed. Health Inf. 22(1), 173–183 (2018)
3. Suk, H.-I., Lee, S.-W., Shen, D., et al.: Deep ensemble learning of sparse regression models for brain disease diagnosis. Med. Image Anal. 37, 101–113 (2017)
4. Korolev, S., Safiullin, A., Belyaev, M., Dodonova, Y.: Residual and plain convolutional neural networks for 3D brain MRI classification. arXiv preprint arXiv:1701.06643 (2017)
5. Lecture Notes in Computer Science;H-I Suk,2013
Cited by 18 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. Alzheimer's Disease (AD) Detection Using Various Machine Learning Techniques: A Systematic Review;2023 6th International Conference on Contemporary Computing and Informatics (IC3I);2023-09-14
2. Artificial Intelligence Approaches for Early Detection and Diagnosis of Alzheimer's Disease: A Review;Academic Journal of Science and Technology;2023-05-05
3. Pulmonary Nodules Binary Classification using CNN and LSTM;2023 10th International Conference on Signal Processing and Integrated Networks (SPIN);2023-03-23
4. Patch-based deep multi-modal learning framework for Alzheimer’s disease diagnosis using multi-view neuroimaging;Biomedical Signal Processing and Control;2023-02
5. Ensemble learning using traditional machine learning and deep neural network for diagnosis of Alzheimer’s disease;IBRO Neuroscience Reports;2022-12
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