Abstract
Clinical guidelines recommend performing left ventricular (LV) linear measurements in B-mode echocardiographic images at the basal level -- typically at the mitral valve leaflet tips -- and aligned perpendicular to the LV long axis along a virtual scanline (SL). However, most automated methods estimate landmarks directly from B-mode images for the measurement task, where even small shifts in predicted points along the LV walls can lead to significant measurement errors, reducing their clinical reliability. A recent semi-automatic method, EnLVAM, addresses this limitation by constraining landmark prediction to a clinician-defined SL and training on generated Anatomical Motion Mode (AMM) images to predict LV landmarks along the same. To enable full automation, a contour-aware SL placement approach is proposed in this work, in which the LV contour is estimated using a weakly supervised B-mode landmark detector. SL placement is then performed by inferring the LV long axis and the basal level-mimicking clinical guidelines. Building on this foundation, we introduce \textit{WiseLVAM} -- a novel, fully automated yet manually adaptable framework for automatically placing the SL and then automatically performing the LV linear measurements in the AMM mode. \textit{WiseLVAM} utilizes the structure-awareness from B-mode images and the motion-awareness from AMM mode to enhance robustness and accuracy with the potential to provide a practical solution for the routine clinical application.
Abstract (translated)
临床指南推荐在B型超声心动图图像的基础水平（通常是在二尖瓣叶尖）进行左心室（LV）线性测量，并且这些测量应该沿着与LV长轴垂直的虚拟扫描线（SL）进行。然而，大多数自动化方法直接从B模式图像估计地标点以完成测量任务，即使预测点在LV壁上的微小偏移也可能导致显著的测量误差，从而降低其临床可靠性。 最近的一种半自动方法EnLVAM通过限制地标预测在由临床医生定义的扫描线上，并使用生成的解剖运动模式（AMM）图像进行训练来解决这一问题。这种方法可以预测沿着相同路径的心室地标位置。为了实现完全自动化，在本研究中提出了一种基于轮廓感知的SL放置方法，其中LV轮廓通过弱监督B模式地标检测器进行估计。然后根据推断出的LV长轴和模仿临床指南中的基础水平来进行扫描线（SL）定位。 在此基础上，我们介绍了\textit{WiseLVAM}——一种全新的、完全自动化的但又可手动调整的框架，用于在AMM模式下自动放置扫描线并进行LV线性测量。该方法利用B模式图像中的结构信息和AMM模式中的运动信息来增强其鲁棒性和准确性，并具有提供实用解决方案以供常规临床应用的潜力。
URL
https://arxiv.org/abs/2508.12023
