RMID: A Novel and Efficient Image Descriptor for Mammogram Mass Classification
Author:
Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-18058-4_18
Reference30 articles.
1. http://www.who.int/cancer/prevention/diagnosis-screening/breast-cancer/en/ . Accessed 15 Feb 2018
2. Skaane, P., Hofvind, S., Skjennald, A.: Randomized trial of screen-film versus full-field digital mammography with soft-copy reading in population-based screening program: follow-up and final results of Oslo II study. Radiology 244(3), 708–17 (2007)
3. Pisano, E.D., Hendrick, R.E., Yaffe, M.J.: for the Digital Mammographic Imaging Screening Trial (DMIST) Investigators Group: Diagnostic accuracy of digital versus film mammography: exploratory analysis of selected population subgroups in DMIST. Radiology 246(2), 376–83 (2008)
4. Moura, D.C., López, M.A.G.: An evaluation of image descriptors combined with clinical data for breast cancer diagnosis. Int. J. Comput. Assist. Radiol. Surg. 8, 561–574 (2013)
5. Constantinidis, A.S., Fairhurst, M.C., Rahman, A.F.R.: A new multi-expert decision combination algorithm and its application to the detection of circumscribed masses in digital mammograms. Pattern Recognit. 34(8), 1527–1537 (2001)
Cited by 8 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. Breast Cancer Mass Classification Using Machine Learning, Binary-Coded Genetic Algorithms and an Ensemble of Deep Transfer Learning;The Computer Journal;2023-04-24
2. A review on machine learning techniques for the assessment of image grading in breast mammogram;International Journal of Machine Learning and Cybernetics;2022-04-01
3. Mammogram Mass Classification: A CNN-Based Technique Applied to Different Age Groups;Communications in Computer and Information Science;2022
4. Architectural Distortion-Based Digital Mammograms Classification Using Depth Wise Convolutional Neural Network;Biology;2021-12-23
5. Classification of Mammogram Masses Using GLCM on LBP and Non-overlapping Blocks of Varying Sizes;Proceedings of International Conference on Data Science and Applications;2021-11-23
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