Advances in AI-powered photorealistic ultrasound visualization techniques: A survey

IF 4.4 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Visual Informatics Pub Date : 2026-09-01 Epub Date: 2026-04-08 DOI:10.1016/j.visinf.2026.100323
Chenyang Zhao, Zhuofan Deng, Qiong Zeng, Fan Zhong, Lin Lu, Wenhua Zhang, Changhe Tu
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引用次数: 0

Abstract

Ultrasound data visualization is essential for diagnosis, anomaly detection, and doctor-patient communication. In recent years, real-time 3D ultrasound and rendering technologies have matured, and leading international ultrasound vendors such as GE Healthcare and Philips have incorporated realistic rendering techniques into ultrasound data visualization, achieving high image quality critical for both diagnostic and display purposes. However, due to the inherently low signal-to-noise ratio and occlusions in ultrasound data, generating highly realistic visualizations remains challenging. Artificial intelligence (AI) offers new opportunities to enhance ultrasound visualization by improving data reconstruction quality, speckle noise reduction, and physically based rendering. In this survey, we review AI-powered approaches across the ultrasound visualization pipeline, building on traditional techniques in data reconstruction, data preprocessing, and realistic rendering, highlighting how AI techniques address the unique characteristics of ultrasound data. Finally, we discuss emerging trends and future directions toward increasingly lifelike and intelligent ultrasound visualization.
人工智能驱动的逼真超声可视化技术进展综述
超声数据可视化对诊断、异常检测和医患沟通至关重要。近年来,实时3D超声和渲染技术已经成熟,GE医疗和飞利浦等领先的国际超声供应商已经将逼真的渲染技术纳入超声数据可视化,实现了诊断和显示目的的高图像质量。然而,由于超声数据固有的低信噪比和闭塞,产生高度逼真的可视化仍然具有挑战性。人工智能(AI)通过提高数据重建质量、降低斑点噪声和基于物理的渲染,为增强超声可视化提供了新的机会。在本调查中,我们回顾了人工智能在超声可视化管道中的应用,在数据重建、数据预处理和逼真渲染等传统技术的基础上,重点介绍了人工智能技术如何解决超声数据的独特特征。最后,我们讨论了越来越逼真和智能超声可视化的新兴趋势和未来方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Visual Informatics
Visual Informatics Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
6.70
自引率
3.30%
发文量
33
审稿时长
79 days
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