机械与电子2025，Vol.43Issue(11)：3-7,14,6.
基于隐式神经网络的超声图像重建方法
Implicit Neural Representation-based Ultrasound Image Reconstruction
摘要
Abstract
To address the challenges of traditional 2D ultrasound in representing 3D tissue structures and its dependence on probe angles and limited physical modeling,this paper proposes a 3D reconstruction method combining implicit neural networks with ultrasound imaging models.By constructing an MLP net-work with spatial coordinates as input,it predicts physical properties of the medium and enhances high-frequency detail expression through positional encoding.The integration of energy attenuation,reflection,and scattering modeling improves the realism and clarity of images from new viewpoints.Experimental re-sults show that this method outperforms traditional voxel interpolation and NeRF in SSIM,LPIPS and PSNR,significantly enhancing structural fidelity and visual quality.关键词
超声成像/隐式神经网络/神经辐射场/体积渲染Key words
ultrasound imaging/implicit neural representation/neural radiance field/volume rendering分类
信息技术与安全科学引用本文复制引用
郭孜文,付庄,张志谊..基于隐式神经网络的超声图像重建方法[J].机械与电子,2025,43(11):3-7,14,6.基金项目
医工交叉项目(YG2019ZDA17,ZH2018QNB23) （YG2019ZDA17,ZH2018QNB23）
国家自然科学基金面上项目(61973210) （61973210）
