Methods and systems for determining an optimal depth and ZOOM setting for ultrasound scans

AI-driven ultrasound systems automatically determine optimal depth and zoom settings, addressing the challenge of suboptimal imaging in rural areas by enhancing diagnostic accuracy and efficiency.

WO2026131393A1PCT designated stage Publication Date: 2026-06-25KONINKLIJKE PHILIPS NV
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Patent Information

Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
KONINKLIJKE PHILIPS NV
Filing Date
2025-12-10
Publication Date
2026-06-25

AI Technical Summary

Technical Problem

In rural and under-resourced communities, the scarcity of ultrasound imaging and lack of trained healthcare workers hampers the ability to obtain suitable ultrasound images for fetal care due to challenges in adjusting depth and zoom settings, leading to suboptimal imaging and diagnostic inefficiencies.

Method used

A computer-implemented method using artificial intelligence (AI) models to automatically determine optimal depth and zoom settings for ultrasound scans by analyzing multiple images, detecting fetal anatomies, and adjusting settings accordingly, reducing reliance on manual expertise.

Benefits of technology

Enhances the accuracy and consistency of ultrasound imaging by automating depth and zoom adjustments, ensuring relevant anatomical features are captured, thereby improving diagnostic utility and reducing the need for repeated scans.

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Abstract

Apparatuses, systems, and methods for determining an optimal depth and zoom setting for ultrasound scans may cause an ultrasound probe to acquire a plurality of images acquired at a corresponding plurality of depths, analyze, using an artificial intelligence (AI) model, data corresponding to the plurality of images to estimate a depth setting and a zoom setting for performing ultrasound scanning, and cause the ultrasound probe to perform an ultrasound scan based on the depth setting and the zoom setting. In some instances, the system may analyze, using the AI model, data corresponding to the plurality of images to estimate a zoom setting for performing ultrasound scanning and cause the ultrasound probe to perform an ultrasound scan based on the zoom setting. In some implementations, the system may detect fetal anatomies using the AI model.
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