Design, analysis and implementation of efficient deep learning frameworks for brain tumor classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-022-13545-0.pdf
Reference45 articles.
1. Abiwinanda N, Hanif M, Hesaputra ST, Handayani A, Mengko TR (2019) Brain tumor classification using convolutional neural network. In: World congress on medical physics and biomedical engineering 2018. Springer, Singapore, pp 183–189
2. Afshar P, Plataniotis KN, Mohammadi A (2019) Capsule networks for brain tumor classification based on MRI images and coarse tumor boundaries. In: ICASSP 2019-2019 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 1368–1372
3. Buetow PC, Smirniotopoulos JG, Done S (1990) Congenital brain tumors: a review of 45 cases. AJR Am J Roentgenol 155(3):587–593
4. Cascio D, Taormina V, Raso G (2019) Deep CNN for IIF images classification in autoimmune diagnostics. Appl Sci 9(8):1618
5. Cheng J (2017) Brain tumor dataset (version 5). Figshare. Retrieved 16 November 2020 from https://doi.org/10.6084/m9.figshare.1512427.v5
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. Deep learning on medical image analysis;CAAI Transactions on Intelligence Technology;2024-06-24
3. Cancerous and Non-Cancerous MRI Classification Using Dual DCNN Approach;Bioengineering;2024-04-23
4. Brain tumor recognition from multimodal magnetic resonance images using wavelet texture features and optimized artificial neural network;Multimedia Tools and Applications;2024-02-10
5. Brain Tumor Medical Image Diagnostic Network Deployed on Low-Cost Embedded Devices;2024 4th International Conference on Neural Networks, Information and Communication (NNICE);2024-01-19
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