Multi-resolution tone mapping for high dynamic range medical ultrasound images

Area of Science:

• Medical Imaging
• Obstetrics and Gynecology
• Biomedical Engineering

Background:

• Ultrasound is crucial for fetal anomaly detection and pregnancy monitoring.
• Image quality in ultrasound is often compromised in obese patients due to reduced contrast resolution.
• High dynamic range (HDR) ultrasound images present challenges for optimal visualization.

Purpose of the Study:

• To develop and preliminarily validate a novel tone-mapping algorithm for enhancing contrast resolution in HDR ultrasound images.
• To improve image quality for better fetal anomaly detection in challenging patient populations.
• To enhance visualization of fetal anatomy, specifically fetal kidneys.

Main Methods:

• A novel tone-mapping algorithm utilizing multi-resolution fusion with depth-adaptive weighting and depth compensation was developed.
• The algorithm was applied to high dynamic range (HDR) ultrasound images.
• The method focused on enhancing contrast, tissue differentiation, noise reduction, and detail preservation.

Main Results:

• Quantitative evaluation on 20 fetal ultrasound images showed a 5.4% mean increase in entropy.
• Mean generalized contrast-to-noise ratio (gCNR) improvements were observed: 15.79% (kidneys vs. fluid), 8.93% (far-field objects vs. fluid), and 17.39% (kidneys vs. adjacent tissues).
• The algorithm demonstrated superior performance compared to an existing method.

Conclusions:

• The developed tone-mapping algorithm effectively enhances contrast resolution in HDR ultrasound images.
• Improved anatomical visualization, particularly of fetal kidneys, was achieved, indicating potential clinical relevance for obstetric ultrasound.
• This technique offers a promising solution for overcoming image quality limitations in obese patients.