首页> 外文会议>Chinese Automation Congress >Global Segmentation-aided Local Masses Detection in X-ray Breast Images
【24h】

Global Segmentation-aided Local Masses Detection in X-ray Breast Images

机译:X线乳房图像中的全局分割辅助局部肿块检测

获取原文

摘要

Breast cancer, as one of the most leading cancers for women, has attached more and more attention. Early image-based detection of masses for mammogram screening plays a crucial role for radiological diagnosis. In this paper, we propose to incorporate global and local information for accurate masses detection. Specifically, we improve a local ROI-based CNN framework which is named as YOLO for coarse mass localization, followed by an improved U-net structure to incorporate global information for fine mass detection. Experimental results on benchmark dataset of INbreast show that our proposed method can achieve preferable results.
机译:乳腺癌作为女性最主要的癌症之一,受到越来越多的关注。早期基于图像的乳房X线筛查肿块检测对放射学诊断至关重要。在本文中,我们建议合并全局和局部信息以进行精确的质量检测。具体来说,我们改进了一个基于ROI的本地CNN框架,该框架被称为YOLO,用于粗略的质量定位,然后是经过改进的U-net结构,以合并用于精细质量检测的全局信息。在INbreast基准数据集上的实验结果表明,本文提出的方法可以取得较好的结果。

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