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Comparison of two-dimensional synthesized mammograms versus original digital mammograms: a quantitative assessment
Medical & Biological Engineering & Computing ( IF 3.2 ) Pub Date : 2021-01-14 , DOI: 10.1007/s11517-021-02313-1
Maxine Tan 1, 2 , Mundher Al-Shabi 1 , Wai Yee Chan 3 , Leya Thomas 3 , Kartini Rahmat 3 , Kwan Hoong Ng 3
Affiliation  

This study objectively evaluates the similarity between standard full-field digital mammograms and two-dimensional synthesized digital mammograms (2DSM) in a cohort of women undergoing mammography. Under an institutional review board–approved data collection protocol, we retrospectively analyzed 407 women with digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) examinations performed from September 1, 2014, through February 29, 2016. Both FFDM and 2DSM images were used for the analysis, and 3216 available craniocaudal (CC) and mediolateral oblique (MLO) view mammograms altogether were included in the dataset. We analyzed the mammograms using a fully automated algorithm that computes 152 structural similarity, texture, and mammographic density–based features. We trained and developed two different global mammographic image feature analysis–based breast cancer detection schemes for 2DSM and FFDM images, respectively. The highest structural similarity features were obtained on the coarse Weber Local Descriptor differential excitation texture feature component computed on the CC view images (0.8770) and MLO view images (0.8889). Although the coarse structures are similar, the global mammographic image feature–based cancer detection scheme trained on 2DSM images outperformed the corresponding scheme trained on FFDM images, with area under a receiver operating characteristic curve (AUC) = 0.878 ± 0.034 and 0.756 ± 0.052, respectively. Consequently, further investigation is required to examine whether DBT can replace FFDM as a standalone technique, especially for the development of automated objective-based methods.

Graphical abstract



中文翻译:

二维合成乳房 X 光照片与原始数字乳房 X 光照片的比较:定量评估

本研究客观地评估了一组接受乳房 X 光检查的女性中标准全视野数字乳房 X 线照片和二维合成数字乳房 X 线照片 (2DSM) 之间的相似性。根据机构审查委员会批准的数据收集协议,我们回顾性分析了 2014 年 9 月 1 日至 2016 年 2 月 29 日期间进行数字乳房断层合成 (DBT) 和全视野数字乳房 X 光检查 (FFDM) 检查的 407 名女性。 FFDM 和 2DSM图像用于分析,并且数据集中总共包含 3216 个可用的颅尾 (CC) 和中间侧斜 (MLO) 视图乳房 X 光照片。我们使用全自动算法分析了乳房 X 线照片,该算法可计算 152 种结构相似性、纹理和基于乳房 X 线照相密度的特征。我们分别针对 2DSM 和 FFDM 图像训练和开发了两种不同的基于全局乳房 X 线图像特征分析的乳腺癌检测方案。在 CC 视图图像 (0.8770) 和 MLO 视图图像 (0.8889) 上计算的粗略 Weber Local Descriptor 差分激励纹理特征分量上获得了最高的结构相似性特征。尽管粗略结构相似,但在 2DSM 图像上训练的基于全局乳房 X 线图像特征的癌症检测方案优于在 FFDM 图像上训练的相应方案,接收器操作特征曲线下的面积 (AUC) = 0.878 ± 0.034 和 0.756 ± 0.052,分别。因此,需要进一步调查以检验 DBT 是否可以替代 FFDM 作为独立技术,

图形概要

更新日期:2021-01-15
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