Suppr超能文献

诊断性 X 射线乳房摄影与预诊断性 X 射线乳房摄影的自动配准:评估与放射科医生准确性的比较。

Automated registration of diagnostic to prediagnostic x-ray mammograms: evaluation and comparison to radiologists' accuracy.

机构信息

Cancer Research UK Epidemiology and Genetics Group, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, United Kingdom.

出版信息

Med Phys. 2010 Sep;37(9):4530-9. doi: 10.1118/1.3457470.

Abstract

PURPOSE

To compare and evaluate intensity-based registration methods for computation of serial x-ray mammogram correspondence.

METHODS

X-ray mammograms were simulated from MRIs of 20 women using finite element methods for modeling breast compressions and employing a MRI/x-ray appearance change model. The parameter configurations of three registration methods, affine, fluid, and free-form deformation (FFD), were optimized for registering x-ray mammograms on these simulated images. Five mammography film readers independently identified landmarks (tumor, nipple, and usually two other normal features) on pairs of diagnostic and corresponding prediagnostic digitized images from 52 breast cancer cases. Landmarks were independently reidentified by each reader. Target registration errors were calculated to compare the three registration methods using the reader landmarks as a gold standard. Data were analyzed using multilevel methods.

RESULTS

Between-reader variability varied with landmark (p < 0.01) and screen (p = 0.03), with between-reader mean distance (mm) in point location on the diagnostic/prediagnostic images of 2.50 (95% CI 1.95, 3.15)/2.84 (2.24, 3.55) for nipples and 4.26 (3.43, 5.24)/4.76 (3.85, 5.84) for tumors. Registration accuracy was sensitive to the type of landmark and the amount of breast density. For dense breasts (> or = 40%), the affine and fluid methods outperformed FFD. For breasts with lower density, the affine registration surpassed both fluid and FFD. Mean accuracy (mm) of the affine registration varied between 3.16 (95% CI 2.56, 3.90) for nipple points in breasts with density 20%-39% and 5.73 (4.80, 6.84) for tumor points in breasts with density < 20%.

CONCLUSIONS

Affine registration accuracy was comparable to that between independent film readers. More advanced two-dimensional nonrigid registration algorithms were incapable of increasing the accuracy of image alignment when compared to affine registration.

摘要

目的

比较和评估基于强度的配准方法,以计算一系列 X 射线乳房摄影的对应关系。

方法

使用有限元方法模拟 20 名女性的 MRI 来建模乳房压缩,并采用 MRI/X 射线外观变化模型。针对在这些模拟图像上对 X 射线乳房摄影进行配准,对三种配准方法(仿射、流体和自由变形(FFD))的参数配置进行了优化。52 例乳腺癌患者的诊断和相应预测数字图像对的 5 位乳腺摄影读者独立地识别出肿瘤、乳头和通常另外两个正常特征的标志点。每个读者都独立地重新识别标志点。以读者标志点作为金标准,计算目标配准误差以比较三种配准方法。使用多水平方法分析数据。

结果

不同读者之间的变异性因标志点(p < 0.01)和屏幕(p = 0.03)而异,在诊断/预测图像上的标志点位置的不同读者之间的平均距离(mm)为 2.50(95%CI 1.95,3.15)/2.84(2.24,3.55)对于乳头和 4.26(3.43,5.24)/4.76(3.85,5.84)对于肿瘤。配准精度对标志点的类型和乳房密度的量敏感。对于致密乳房(≥40%),仿射和流体方法优于 FFD。对于密度较低的乳房,仿射配准优于流体和 FFD。仿射配准的平均精度(mm)在乳房密度为 20%-39%的乳头点之间为 3.16(95%CI 2.56,3.90),而在乳房密度<20%的肿瘤点之间为 5.73(4.80,6.84)。

结论

仿射配准的准确性与独立胶片读者相当。与仿射配准相比,更先进的二维非刚性配准算法无法提高图像对齐的准确性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验