MoNetV2: Enhanced Motion Network for Freehand 3D Ultrasound Reconstruction

Abstract--Three-dimensional (3D) ultrasound (US) aims to provide sonographers with the spatial relationships of ana tomical structures, playing a crucial role in clinical diagnosis. R ecently, deep-learning-based freehand 3D US has made significant advancements. However, i mage-only reconstruction poses difficulties in reducing cumulat ive drift and further improving reconstruction accuracy, particula rly in scenarios involving complex motion trajectories. In this c ontext, we propose an enhanced motion network (MoNetV2) to enhance the accuracy and generalizability of reconstruction under diverse scanning velocities and tactics. First, we propose a sensor -based temporal and multi-branch structure that fuses image and mo tion information from a velocity perspective to improve image-o nly reconstruction accuracy. Second, we devise an online multi -level consistency constraint that exploits the inherent consist ency of scans to handle various scanning velocities and tactics. Th is constraint exploits both scan-level velocity consistency, path-level appearance consistency, and patch-level motion consisten cy to supervise inter-frame transformation estimation. Third, we distill an online multi-modal self-supervised strategy that lever ages the correlation between network estimation and motion informa tion to further reduce cumulative errors. Extensive experiment s clearly demonstrate that MoNetV2 surpasses existing metho ds in both reconstruction quality and generalizability perfo rmance across three large datasets. L TRASOUND (US) imaging plays an important role in clinical monitoring and diagnosis because of its non-invasiveness, real-time, and mobility [ 1 ]. This work was supported by the National Natural Science Foun dation of China (Nos. Jin Wang and Litao Sun are with the Cancer C enter, Department of Ultrasound Medicine, Zhejiang Provincial Pe ople's Hospital, Affiliated People's Hospital of Hangzhou Medical Colle ge, Hangzhou, Zhejiang, China. Wei Han is with the Department of Health Man agement Center, Qilu Hospital, Cheeloo College of Medicine, Shando ng University, Jinan, Shandong, China. Its applications span vari ous fields such as heart [ 2 ], fetus [ 3 ], breast [ 4 ], and liver [ 5 ]. Traditional 3D US imaging methods encompass mechanical, phased array, and freehand techniques. Mechanical and phas ed array imaging often suffer from specialized and expensive hardware with a limited field of view.