Evolutionary intelligence for breast lesion detection in ultrasound images: A wavelet modulus maxima and SVM based approach
Author:
Affiliation:
1. Department of Electronics Engineering, Model Engineering College, Kochi, India
2. Department of Computer Engineering, KMEA College of Engineering, Kerala, India
3. Lakeshore Hospital, Kochi, Kerala, India
Publisher
IOS Press
Subject
Artificial Intelligence,General Engineering,Statistics and Probability
Reference34 articles.
1. American cancer society: Cancer facts and figures, 2018.
2. Combined screening with ultrasound and mammography vs mammography alone in women at elevated risk of breast cancer;Berg;Journal of American Medical Association,2008
3. A novel algorithm for initial lesion detection in ultrasound breast images;Yap;Journal of applied clinical medical physics,2008
4. Computer-aided detection/diagnosis of breast cancer in mammography and ultrasound: a review;Jalalian;Clinical imaging,2013
5. Analysis of sonographic features for the differentiation of benign and malignant breast tumors of different size;Chen;Ultrasound Obstet Gynecol,2004
Cited by 5 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. The Application of Two-Dimensional Continuous Wavelet Transform Based on Active Infrared Thermography for Subsurface Defect Detection in Concrete Structures;Buildings;2022-11-13
2. Artificial Intelligence Predicted Overall Survival and Classified Mature B-Cell Neoplasms Based on Immuno-Oncology and Immune Checkpoint Panels;Cancers;2022-10-28
3. Diagnostic Strategies for Breast Cancer Detection: From Image Generation to Classification Strategies Using Artificial Intelligence Algorithms;Cancers;2022-07-15
4. A Characterization Approach for the Review of CAD Systems Designed for Breast Tumor Classification Using B-Mode Ultrasound Images;Archives of Computational Methods in Engineering;2021-07-08
5. Breast ultrasound tumour classification: A Machine Learning—Radiomics based approach;Expert Systems;2021-05-11
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