Ultrasound Measurement Condition Inference for Automated Image Quantification

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Solution Overview

Problem

Existing ultrasound diagnosis systems lack an efficient method for automatically setting measurement conditions for various measurements such as distance, area, and volume, relying on manual operator input.

Innovation Solution

An ultrasound diagnosis apparatus that utilizes a trained model to infer and set measurement conditions for ultrasound image data, including a generation unit, inference unit, and measurement unit to automate the process.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual operator input is used to set measurement conditions, then operator control and flexibility are maintained, but measurement efficiency and productivity are reduced

Engineering Contradiction:

Improvemeasurement efficiencyVSAvoidoperator control

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

The system automatically sets measurement conditions by having the measurement condition setting unit infer conditions directly from ultrasound image data using a trained model, eliminating the need for manual operator input and significantly improving measurement efficiency while maintaining accurate and context-appropriate measurement settings

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the manual mechanical process of operator input with an automated inference system using machine learning models that process ultrasound image data to determine appropriate measurement conditions, thereby increasing productivity without sacrificing measurement accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If automated measurement condition setting is implemented using a trained model, then measurement efficiency and productivity are improved, but device complexity increases

Engineering Contradiction:

Improvemeasurement efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system performs preliminary training of the machine learning model using labeled ultrasound image data and measurement conditions before deployment. This pre-training phase creates a ready-to-use inference system that can automatically set measurement conditions without requiring complex real-time processing during actual measurements, thereby improving efficiency while managing complexity

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces a trained inference model as an intermediary between the ultrasound image data and the measurement condition setting process. This intermediary component handles the complex analysis and decision-making, allowing the rest of the system to remain relatively simple while achieving high measurement efficiency through automated condition inference

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS12544041B2Ultrasound diagnosis apparatus, measurement condition setting method, and non-transitory computer-readable storage medium

Publication Date: 2026.02.10 CANON KK

AI summary

A generation unit that generates ultrasound image data on a subject, an inference unit that infers at least one measurement condition candidate for the ultrasound image data on the subject using a trained model trained with measurement conditions set for ultrasound image data as supervised data, a measurement condition setting unit that sets a measurement condition for the ultrasound image data on the subject using the at least one inferred measurement condition candidate, and a measurement unit that makes a measurement on the ultrasound image data on the subject based on the set measurement condition.