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arXiv · 2506.22063

EnLVAM: Enhanced Left Ventricle Linear Measurements Utilizing Anatomical Motion Mode

Durgesh K. Singh·Ahcene Boubekki·Qing Cao·Svein Arne Aase·Robert Jenssen·Michael Kampffmeyer
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Abstract

Linear measurements of the left ventricle (LV) in the Parasternal Long Axis (PLAX) view using B-mode echocardiography are crucial for cardiac assessment. These involve placing 4-6 landmarks along a virtual scanline (SL) perpendicular to the LV axis near the mitral valve tips. Manual placement is time-consuming and error-prone, while existing deep learning methods often misalign landmarks, causing inaccurate measurements. We propose a novel framework that enhances LV measurement accuracy by enforcing straight-line constraints. A landmark detector is trained on Anatomical M-Mode (AMM) images, computed in real time from B-mode videos, then transformed back to B-mode space. This approach addresses misalignment and reduces measurement errors. Experiments show improved accuracy over standard B-mode methods, and the framework generalizes well across network architectures. Our semi-automatic design includes a human-in-the-loop step where the user only places the SL, simplifying interaction while preserving alignment flexibility and clinical relevance.

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Durgesh K. Singh, Ahcene Boubekki, Qing Cao, Svein Arne Aase, Robert Jenssen, Michael Kampffmeyer. 2025-06-27. EnLVAM: Enhanced Left Ventricle Linear Measurements Utilizing Anatomical Motion Mode. https://arxiv.org/abs/2506.22063

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