首页> 外文会议>IEEE International Symposium on Biomedical Imaging >Signet Ring Cells Detection in Histology Images with Similarity Learning
【24h】

Signet Ring Cells Detection in Histology Images with Similarity Learning

机译:具有相似性学习的组织学图像中的印戒细胞检测

获取原文

摘要

The detection of signet ring cells in histology images is of great value in clinical practice. However, several reasons such as appearance variations and lack of well-labelled data make it a challenging task. Considering the intrinsic characteristics of signet ring cell images, a dedicated similarity learning network is designed in this paper to help the discovery of distinctive feature representations for ring cells. Specifically, we adapt the region proposal network and add an embedding layer to enable similarity learning for training the model. Experimental results show that similarity learning can strengthen the performance of the state-of-the-art and makes our approach competent for the task of signet ring cell detection.
机译:组织学图像中印戒细胞的检测在临床实践中具有重要价值。但是,由于外观变化和缺少标签清晰的数据等多种原因,这使其成为一项具有挑战性的任务。考虑到图章环细胞图像的内在特征,本文设计了专用的相似性学习网络来帮助发现环细胞的独特特征表示。具体来说,我们调整区域提案网络并添加嵌入层以启用相似性学习以训练模型。实验结果表明,相似性学习可以增强最新技术的性能,并使我们的方法能够胜任图章环细胞检测的任务。

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