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. • The photorealistic ultrasound visualization pipeline is identified and introduced. • Both traditional and AI-powered approaches in each pipeline module are categorized and reviewed. The rendering feature supported and performance of each method is illustrated. • Current trends and future directions of the photo-realistic ultrasound visualization pipeline are discussed.
Zhao et al. (2026) studied this question.