• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Academic radiology >Comparative analysis of data collection methods for individualized modeling of radiologists' visual similarity judgments in mammograms
【24h】

Comparative analysis of data collection methods for individualized modeling of radiologists' visual similarity judgments in mammograms

机译：乳房X线图中的辐射学师视觉相似性判断个性化建模数据收集方法的比较分析

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Rationale and Objectives: We conducted an observer study to investigate how the data collection method affects the efficacy of modeling individual radiologists' judgments regarding the perceptual similarity of breast masses on mammograms. Materials and Methods: Six observers of varying experience levels in breast imaging were recruited to assess the perceptual similarity ofmammographic masses. The observers' subjective judgments were collected using (i) a rating method, (ii) a preference method, and (iii)ahybrid method combining rating and ranking. Personalized user models were developed with the collected data to predict observers' opinions. The relative efficacy of each data collection method was assessed based on the classification accuracy of the resulting usermodels. Results: The average accuracy of the user models derived from data collected with the hybrid method was 55.5±1.5%. The models were significantly more accurate ( P < .0005) than those derived from the rating (45.3±3.5%) and the preference (40.8±5%) methods. Onaverage, the rating data collection method was significantly faster than the other two methods ( P < .0001). No time advantage was observed between the preference and the hybrid methods. Conclusions: A hybrid method combining rating and ranking is an intuitive and efficient way for collecting subjective similarity judgments to model human perceptual opinions with a higher accuracy than other, more commonly used data collection methods.
机译：理由和目标：我们进行了一个观察者研究，调查数据收集方法如何影响为乳房X线图上乳腺菌群体的感知相似性建模的疗效。材料和方法：招募了六种不同体验水平的六种观察者，以评估泻眼的感知相似性。使用（i）评级方法，（ii）偏好方法，（iii）结合额定值和排名的偏好方法，（ii）收集观察者的主观判断。个性化用户模型是通过收集的数据开发的，以预测观察员的意见。基于所得USMODELS的分类精度评估每个数据收集方法的相对功效。结果：从采用混合方法收集的数据的用户模型的平均精度为55.5±1.5％。该模型明显更准确（P <.0005），而不是衍生的级别（45.3±3.5％）和偏好（40.8±5％）方法。 OnaVerage，评级数据收集方法明显比其他两种方法更快（P <.0001）。在偏好和混合方法之间没有观察到时间优势。结论：混合方法结合等级和排名是一种直观和有效的方法，用于收集主观相似度判断，以利用更高的准确性模拟人类感知意见而不是其他更常用的数据收集方法。

著录项

  • 来源
    《Academic radiology》 |2013年第11期|共10页
  • 作者

    TourassiG.; YoonH.-J.; XuS.; Morin-DucoteG.; HudsonK.;

  • 作者单位

    Biomedical Science and Engineering Center Oak Ridge National Laboratory 1 Bethel Valley Road P.O;

    Biomedical Science and Engineering Center Oak Ridge National Laboratory 1 Bethel Valley Road P.O;

    Biomedical Science and Engineering Center Oak Ridge National Laboratory 1 Bethel Valley Road P.O;

    Department of Radiology University of Tennessee Medical Center at Knoxville Knoxville TN United;

    Department of Radiology University of Tennessee Medical Center at Knoxville Knoxville TN United;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 放射医学;
  • 关键词

    Breast imaging; Mammography; Observer variability; Perception; Visual similarity user modeling;

    机译：乳房成像;乳房X线照相术;观察者变异性;感知;视觉相似性用户建模;

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