首页> 外文会议>International Workshop on Multimodal Retrieval in the Medical Domain >Multimodal Medical Case-Based Retrieval on the Radiology Image and Report: SNUMedinfo at VISCERAL Retrieval Benchmark
【24h】

Multimodal Medical Case-Based Retrieval on the Radiology Image and Report: SNUMedinfo at VISCERAL Retrieval Benchmark

机译:基于多模式的医疗案例的放射图像检索和报告:内脏检索基准测试中的SnumedInfo

获取原文

摘要

This paper describes the participation at the VISCERAL Retrieval benchmark. The task is about retrieving relevant medical cases from radiology image and report. Both query and retrieval datasets are composed of multimodal data. We extracted low-level visual features (SURF) from images and trained a query-specific SVM classifier for image retrieval. For textual retrieval, we estimated relevance with an anatomy-pathology paired RadLexID similarity function. In mixed retrieval, we combined them using weighted Borda-fuse method.
机译:本文介绍了对内脏检索基准的参与。任务是关于从放射学图像和报告中检索相关的医疗案例。查询和检索数据集都由多模式数据组成。我们从图像中提取了低级视觉功能(冲浪)并训练了查询特定的SVM分类器以进行图像检索。对于文本检索,我们估计与解剖学配对的RadlexId相似函数的相关性。在混合检索中,我们将它们组合使用加权BORDA-FUSE方法。

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