AWR-Net: Decoupling Anatomy and Appearance for 3D Fetal Brain Ultrasound Synthesis

2026-09-18

AI Summary

为解决3D胎儿脑部超声数据稀缺问题，提出AWR-Net网络，通过解耦解剖结构和外观特征，结合小波扩散和残差修正生成高质量的超声图像。

Abstract

Three-dimensional fetal brain ultrasound offers non-ionizing, cost-effective imaging with rich spatial information for comprehensive anatomical assessment, yet its development remains limited by scarce data and annotations. In contrast, fetal brain magnetic resonance imaging has advanced further, supported by larger datasets and mature analysis methods. To leverage these resources, anatomical label maps provide a promising modality-invariant bridge for transferring knowledge from fetal brain magnetic resonance imaging to ultrasound. However, generating ultrasound images from label maps remains challenging because anatomy is tightly entangled with ultrasound appearance. To address this challenge, we separate anatomical correspondence learning from ultrasound appearance adaptation at both the data and model levels. Specifically, we propose the anatomy wavelet residual network, a two-stage framework combining wavelet diffusion and residual refinement. The first stage learns to generate volumes from label maps using atlas pairs in the wavelet domain, while the second stage learns bounded residual corrections from real clinical ultrasound in the image domain. This separation enables realistic synthesis with consistent preservation of normal and abnormal anatomy. Experiments on real fetal brain ultrasound show that our method outperforms representative synthesis methods, with normalized cross correlation of 0.518 versus 0.482 and Fréchet Inception Distance of 8.905 versus 13.319 for the strongest baseline. Beyond synthesis quality, volumes generated from fetal brain magnetic resonance imaging label maps also improve downstream segmentation, particularly for severe abnormal cases. Overall, these results highlight the potential of the proposed framework to leverage rich fetal brain magnetic resonance imaging resources for advancing three-dimensional ultrasound analysis.

Problem

• 3D Fetal Brain Ultrasound
• Anatomical Label Maps
• Fetal Brain MRI
• Data Scarcity
• Appearance Entanglement

Innovation

• anatomy wavelet residual network
• wavelet diffusion
• residual refinement
• anatomical correspondence learning
• ultrasound appearance adaptation