...
首页> 外文期刊>Applied Artificial Intelligence >A New Image Mining Approach for Detecting Micro-Calcification in Digital Mammograms
【24h】

A New Image Mining Approach for Detecting Micro-Calcification in Digital Mammograms

机译:检测数字乳腺X线摄影中微钙化的新图像挖掘方法

获取原文
获取原文并翻译 | 示例

摘要

Although mammography is typically the best method to detect breast cancer, it does not recognize 3-20% of the cancer cases. Mammography has established itself as the most efficient technique for detecting tiny cancerous tumor andmicro-calcifications are the most difficult to detect since they are very small (0.1-1.0 mm) and they are almost contrasted against the images background. The main purpose of this paper is to provide a newmethod for the automatic diagnosis of micro-calcification in digital mammograms. It is based on image mining, and the results show 97.35% accuracy, which is improved than the previous works. Tests are based on the standard images data corpus, MIAS. The practical result of this research is registered as an invention in the Patents and Industrial Property Registration Organization numbered as 83119.
机译:尽管乳房X线照相术通常是检测乳腺癌的最佳方法,但不能识别3-20%的癌症病例。乳房X线照相术已经确立为检测微小癌瘤的最有效技术,并且微钙化非常难以检测,因为它们很小(0.1-1.0 mm),并且几乎与图像背景形成对比。本文的主要目的是为数字乳房X线照片中的微钙化提供一种自动诊断的新方法。它是基于图像挖掘的,结果表明准确度为97.35%,比以前的工作有所提高。测试基于标准图像数据语料库MIAS。这项研究的实际结果在专利和工业产权注册组织中注册为发明,编号为83119。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号