Year: 2026
Type: article
Abstract: Ultrasound diagnostics is a key tool in obstetrics for detecting fetal anomalies and monitoring pregnancy, but image quality often declines in obese patients due to reduced contrast resolution. This pilot study develops and preliminarily validates a novel tone-mapping algorithm for enhancing contrast resolution in high dynamic range (HDR) ultrasound images. The method employs multi-resolution fusion with depth-adaptive weighting and depth compensation to improve contrast, enhance tissue differentiation, reduce noise, and preserve fine details. The algorithm was tested on 20 fetal ultrasound images focused on fetal kidney visualization. Quantitative evaluation showed a 5.4% mean increase in entropy and mean generalized contrast-to-noise ratio (gCNR) improvements of 15.79%, 8.93%, and 17.39% between fetal kidneys and amniotic fluid, far-field objects and fluid, and fetal kidneys and adjacent tissues, respectively, compared with an existing method. These results demonstrate improved anatomical visualization, particularly of fetal kidneys, with potential clinical relevance.
Source: PLoS ONE
Language: English
Topic: Image Enhancement Techniques
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,382
OpenAlex ID: W7125013309