基于离散小波变换特征和一种新的矢量量化技术的乳腺癌症乳腺图像分类

A. Sarhan, Radaan Al-Dosari
{"title":"基于离散小波变换特征和一种新的矢量量化技术的乳腺癌症乳腺图像分类","authors":"A. Sarhan, Radaan Al-Dosari","doi":"10.9734/bjast/2017/30420","DOIUrl":null,"url":null,"abstract":"In this paper, a digital mammogram classification system is presented. The proposed system uses the Discrete Wavelet Transform (DWT) to obtain features from the input mammogram image. The proposed system suggests a new algorithm for generating the codebook used by the vector quantization (VQ) algorithm to classify the input mammogram (malignant, benign, or normal). The obtained results on the DDSM database indicate the significant performance and superiority of the proposed method in comparison with the state of the art approaches. Simulation results show that the proposed system achieves a high accuracy and sensitivity.","PeriodicalId":91221,"journal":{"name":"British journal of applied science & technology","volume":"19 1","pages":"1-14"},"PeriodicalIF":0.0000,"publicationDate":"2017-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Mammogram Classification Using Discrete Wavelet Transform Features and a Novel Vector Quantization Technique for Breast Cancer Detection\",\"authors\":\"A. Sarhan, Radaan Al-Dosari\",\"doi\":\"10.9734/bjast/2017/30420\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a digital mammogram classification system is presented. The proposed system uses the Discrete Wavelet Transform (DWT) to obtain features from the input mammogram image. The proposed system suggests a new algorithm for generating the codebook used by the vector quantization (VQ) algorithm to classify the input mammogram (malignant, benign, or normal). The obtained results on the DDSM database indicate the significant performance and superiority of the proposed method in comparison with the state of the art approaches. Simulation results show that the proposed system achieves a high accuracy and sensitivity.\",\"PeriodicalId\":91221,\"journal\":{\"name\":\"British journal of applied science & technology\",\"volume\":\"19 1\",\"pages\":\"1-14\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-01-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"British journal of applied science & technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.9734/bjast/2017/30420\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"British journal of applied science & technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9734/bjast/2017/30420","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

本文介绍了一种数字乳腺X线照片分类系统。所提出的系统使用离散小波变换(DWT)从输入的乳房X光图像中获得特征。所提出的系统提出了一种新的算法,用于生成矢量量化(VQ)算法所使用的码本,以对输入的乳房X光照片(恶性、良性或正常)进行分类。在DDSM数据库上获得的结果表明,与现有技术相比,所提出的方法具有显著的性能和优越性。仿真结果表明,该系统具有较高的精度和灵敏度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Mammogram Classification Using Discrete Wavelet Transform Features and a Novel Vector Quantization Technique for Breast Cancer Detection
In this paper, a digital mammogram classification system is presented. The proposed system uses the Discrete Wavelet Transform (DWT) to obtain features from the input mammogram image. The proposed system suggests a new algorithm for generating the codebook used by the vector quantization (VQ) algorithm to classify the input mammogram (malignant, benign, or normal). The obtained results on the DDSM database indicate the significant performance and superiority of the proposed method in comparison with the state of the art approaches. Simulation results show that the proposed system achieves a high accuracy and sensitivity.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Superluminal Hydrogen Atom in a Constant Magnetic Field in (3+1)-dimensional Spacetime (II) Climate Change and Its Impact on Nutritional Status and Health of Children Effect of Bio-stimulants on Improving Floral Characteristics, Yield and Quality of Apple cv. Red Delicious An Analysis of the Potential, Constraints and Strategies for Development of Marirangwe Farm (A Project of the Women’s University in Africa) Choosing the Optimal Segmentation Level for POS Tagging of the Quranic Arabic
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1