GSO-CNN-based model for the identification and classification of thyroid nodule in medical USG images
Author:
Publisher
Springer Science and Business Media LLC
Subject
Urology
Link
https://link.springer.com/content/pdf/10.1007/s13721-022-00388-w.pdf
Reference47 articles.
1. Ajilisa OA, Jagathyraj VP, Sabu MK (2020) Computer-aided diagnosis of thyroid nodule from ultrasound images using transfer learning from deep convolutional neural network models. In 2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA). IEEE. pp. 237–241
2. Awan SE, Sohel F, Sanfilippo FM, Bennamoun M, Dwivedi G (2018) Machine learning in heart failure: ready for prime time. Curr Opin Cardiol 33(2):190–195
3. Boesch G (2022) “Deep residual networks (Resnet-50), Published 2022. https://viso.ai/deep-learning/resnet-residual-neural-network/. Accessed 15 Sep 2022
4. Cinaglia P, Tradigo G, Cascini GL, Zumpano E, Veltri P (2018) A framework for the decomposition and features extraction from lung DICOM images. In Proceedings of the 22nd international database engineering & applications symposium. pp. 31–36.
5. Esteva A, Kuprel B, Novoa RA, Ko J, Swetter SM, Blau HM, Thrun S (2017) Dermatologist-level classification of skin cancer with deep neural networks. Nature 542(7639):115–118
Cited by 2 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. Shape-margin knowledge augmented network for thyroid nodule segmentation and diagnosis;Computer Methods and Programs in Biomedicine;2024-02
2. Ultrasonic Thyroid Nodule Benign-Malignant Classification with Multi-level Features Fusions;2023 8th International Conference on Image, Vision and Computing (ICIVC);2023-07-27
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