• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国卫生研究院文献>Journal of Digital Imaging >Reduction of False-Positive Markings on Mammograms: a Retrospective Comparison Study Using an Artificial Intelligence-Based CAD
【2h】

Reduction of False-Positive Markings on Mammograms: a Retrospective Comparison Study Using an Artificial Intelligence-Based CAD

机译：减少乳房X光照片上的假阳性标记：使用基于人工智能的CAD的回顾性比较研究

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The aim was to determine whether an artificial intelligence (AI)-based, computer-aided detection (CAD) software can be used to reduce false positive per image (FPPI) on mammograms as compared to an FDA-approved conventional CAD. A retrospective study was performed on a set of 250 full-field digital mammograms between January 1, 2013, and March 31, 2013, and the number of marked regions of interest of two different systems was compared for sensitivity and specificity in cancer detection. The count of false-positive marks per image (FPPI) of the two systems was also evaluated as well as the number of cases that were completely mark-free. All results showed statistically significant reductions in false marks with the use of AI-CAD vs CAD (confidence interval = 95%) with no reduction in sensitivity. There is an overall 69% reduction in FPPI using the AI-based CAD as compared to CAD, consisting of 83% reduction in FPPI for calcifications and 56% reduction for masses. Almost half (48%) of cases showed no AI-CAD markings while only 17% show no conventional CAD marks. There was a significant reduction in FPPI with AI-CAD as compared to CAD for both masses and calcifications at all tissue densities. A 69% decrease in FPPI could result in a 17% decrease in radiologist reading time per case based on prior literature of CAD reading times. Additionally, decreasing false-positive recalls in screening mammography has many direct social and economic benefits.
机译：目的是确定与基于FDA批准的常规CAD相比，基于人工智能（AI）的计算机辅助检测（CAD）软件是否可用于减少乳房X线照片上的每幅图像假阳性（FPPI）。在2013年1月1日至2013年3月31日期间，对250幅全视野数字化乳房X线照片进行了回顾性研究，并比较了两种不同系统的标记感兴趣区域的数量，以检测癌症的敏感性和特异性。还评估了两个系统的每个图像的假阳性标记数（FPPI）以及完全没有标记的病例数。所有结果均表明，使用AI-CAD与CAD相比，假标记在统计上有显着减少（置信区间= 95％），而敏感性没有下降。与基于CAD的CAD相比，使用基于AI的CAD可使FPPI总体降低69％，其中钙化的FPPI降低83％，质量的降低56％。几乎一半（48％）的病例没有AI-CAD标记，而只有17％的病例没有常规CAD标记。与CAD相比，在所有组织密度下，AI-CAD的FPPI均显着低于CAD。根据现有的CAD阅读时间文献，FPPI降低69％可能导致每个病例的放射线医生阅读时间减少17％。此外，减少乳腺钼靶筛查的假阳性召回率具有许多直接的社会和经济效益。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

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