合成B模式超声图像
合成B模式超声图像数据集,用于心脏运动分析,提升心脏疾病诊断的准确性和可重复性。
基本信息
资源简介
该数据集由德克萨斯A&M大学研究团队创建,包含从有限元模拟生成的合成B模式超声图像,覆盖心脏多个层面。通过模拟心脏运动,提供基准量以改进超声图像中的运动估计算法,主要用于心脏疾病诊断的准确性和可重复性提升。
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使用方式
数据集说明
合成B模式超声图像 对应论文数据集(arXiv 预印本)。
数据获取指引
- 打开论文页面获取作者与项目信息:https://arxiv.org/abs/2409.04577v1
- 论文 Data Availability / Code Availability 章节标注了数据实际托管位置;
- 获取到实际数据链接后,按对应平台标准方式下载。
论文摘要:Abstract:Brightness mode (B-mode) ultrasound is a common imaging modality in the clinical assessment of several cardiovascular diseases. The utility of ultrasound-based functional indices such as the ejection fraction (EF) and stroke volume (SV) is widely described in diagnosing advanced-stage cardiovascular diseases. Additionally, structural indices obtained through the analysis of cardiac motion have been found to be important in the early-stage assessment of structural heart diseases, such as hypertrophic cardiomyopathy and myocardial infarction. Estimating heterogeneous variations in cardiac motion through B-mode ultrasound imaging is a crucial component of patient care. Despite the benefits of such imaging techniques, motion estimation algorithms are susceptible to variability between vendors due to the lack of benchmark motion quantities. In contrast, finite element (FE) simulations of cardiac biomechanics leverage well-established constitutive models of the myocardium to ensure reproducibility. In this study, we developed a methodology to create synthetic B-mode ultrasound images from FE simulations. The proposed methodology provides a detailed representation of displacements and strains under complex mouse-specific loading protocols of the LV. A comparison between the synthetic images and FE simulations revealed qualitative similarity in displacement patterns, thereby yielding benchmark quantities to improve the reproducibility of motion estimation algorithms. Thus, the study provides a methodology to create an extensive repository of images describing complex motio
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