Classification of stages in cervical cancer MRI by customized CNN and transfer learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Cognitive Neuroscience
Link
https://link.springer.com/content/pdf/10.1007/s11571-021-09777-9.pdf
Reference15 articles.
1. Bonheur S, Štern D, Payer C, Pienn M, Olschewski H, Urschler M (2019) Matwo-capsnet: a multi-label semantic segmentation capsules network. In: International conference on medical image computing and computer-assisted intervention (pp. 664–672). Springer, Cham
2. Deng F, Pu S, Chen X, Shi Y, Yuan T, Pu S (2018) Hyperspectral image classification with capsule network using limited training samples. Sensors 18(9):3153
3. Ghoneim A, Muhammad G, Hossain MS (2020) Cervical cancer classification using convolutional neural networks and extreme learning machines. Futur Gener Comput Syst 102:643–649
4. Goceri E (2020) CapsNet topology to classify tumours from brain images and comparative evaluation. IET Image Proc 14(5):882–889
5. Li HC, Wang WY, Pan L, Li W, Du Q, Tao R (2020) Robust capsule network based on maximum correntropy criterion for hyperspectral image classification. IEEE J Selected Topics Appl Earth Observat Remote Sens 13:738–751
Cited by 4 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. Enhancing the Accuracy of Lymph-Node-Metastasis Prediction in Gynecologic Malignancies Using Multimodal Federated Learning: Integrating CT, MRI, and PET/CT;Cancers;2023-11-03
2. An Evaluative Investigation of Deep Learning Models by Utilizing Transfer Learning and Fine-Tuning for Cervical Cancer Screening of Whole Slide Pap-Smear Images;2023 7th International Conference on Computer Applications in Electrical Engineering-Recent Advances (CERA);2023-10-27
3. An efficient memory reserving-and-fading strategy for vector quantization based 3D brain segmentation and tumor extraction using an unsupervised deep learning network;Cognitive Neurodynamics;2023-04-26
4. HDFCN: A Robust Hybrid Deep Network Based on Feature Concatenation for Cervical Cancer Diagnosis on WSI Pap Smear Slides;BioMed Research International;2023-04-17
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