...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Magnetic resonance imaging: An International journal of basic research and clinical applications >A new perceptual difference model for diagnostically relevant quantitative image quality evaluation: A preliminary study
【24h】

A new perceptual difference model for diagnostically relevant quantitative image quality evaluation: A preliminary study

机译：诊断相关定量图像质量评估的新知觉差异模型：初步研究

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Most objective image quality metrics average over a wide range of image degradations. However, human clinicians demonstrate bias toward different types of artifacts. Here, we aim to create a perceptual difference model based on Case-PDM that mimics the preference of human observers toward different artifacts. Method: We measured artifact disturbance to observers and calibrated the novel perceptual difference model (PDM). To tune the new model, which we call Artifact-PDM, degradations were synthetically added to three healthy brain MR data sets. Four types of artifacts (noise, blur, aliasing or "oil painting" which shows up as flattened, over-smoothened regions) of standard compressed sensing (CS) reconstruction, within a reasonable range of artifact severity, as measured by both PDM and visual inspection, were considered. After the model parameters were tuned by each synthetic image, we used a functional measurement theory pair-comparison experiment to measure the disturbance of each artifact to human observers and determine the weights of each artifact's PDM score. To validate Artifact-PDM, human ratings obtained from a Double Stimulus Continuous Quality Scale experiment were compared to the model for noise, blur, aliasing, oil painting and overall qualities using a large set of CS-reconstructed MR images of varying quality. Finally, we used this new approach to compare CS to GRAPPA, a parallel MRI reconstruction algorithm. Results: We found that, for the same Artifact-PDM score, the human observer found incoherent aliasing to be the most disturbing and noise the least. Artifact-PDM results were highly correlated to human observers in both experiments. Optimized CS reconstruction quality compared favorably to GRAPPA's for the same sampling ratio. Conclusions: We conclude our novel metric can faithfully represent human observer artifact evaluation and can be useful in evaluating CS and GRAPPA reconstruction algorithms, especially in studying artifact trade-offs.
机译：大多数客观的图像质量指标在各种图像质量下降范围内平均。但是，人类临床医生表现出对不同类型伪像的偏见。在这里，我们旨在基于Case-PDM创建一个感知差异模型，该模型模仿人类观察者对不同工件的偏好。方法：我们测量了对观察者的人为干扰，并校准了新型感知差异模型（PDM）。为了调整称为Artifact-PDM的新模型，将退化综合添加到三个健康的大脑MR数据集中。标准压缩感测（CS）重建的四种伪影（噪声，模糊，混叠或“油画”，显示为平坦，过度平滑的区域），在伪影严重性的合理范围内（通过PDM和视觉测量）检查，被认为。在通过每个合成图像调整模型参数之后，我们使用功能测量理论对比较实验来测量每个工件对人类观察者的干扰，并确定每个工件的PDM得分的权重。为了验证Artifact-PDM，我们使用大量CS重建的不同质量的MR图像，将从Double Stimulus连续质量量表实验中获得的人类评级与模型的噪声，模糊，混叠，油画和整体质量进行了比较。最后，我们使用这种新方法将CS与GRAPPA（一种并行的MRI重建算法）进行比较。结果：我们发现，对于相同的Artifact-PDM分数，人类观察者发现不连贯的混叠最令人困扰，而杂音最少。在两个实验中，工件-PDM结果与人类观察者高度相关。在相同的采样率下，优化的CS重建质量优于GRAPPA。结论：我们得出结论，我们的新度量标准可以忠实地代表人类观察者的人工产物评估，并且可以用于评估CS和GRAPPA重建算法，尤其是在研究人工产物的权衡方面。

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