Feedback-Based Quality Assessment for Medical Imaging

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Solution Overview

Problem

In medical imaging systems, especially in geographically distributed radiological centers, manual selection of acquisition parameters can lead to inconsistencies and inferior image quality due to outdated protocols and lack of synchronization, resulting in motion artifacts and incorrect fields of view, which can lead to erroneous diagnoses and re-acquisition challenges.

Innovation Solution

A feedback-based quality assessment method and system that uses a machine learning module to predict physician satisfaction levels based on collected feedback, selecting reference images with associated acquisition parameters to configure medical imaging devices, ensuring consistent and high-quality image acquisition across sites, and allowing continuous quality improvement through a feedback loop.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If manual selection of acquisition parameters is used, then technicians can adjust parameters based on experience, but inconsistencies and inferior image quality occur due to outdated protocols and lack of synchronization

Engineering Contradiction:

Improvemanual parameter selectionVSAvoidimage quality consistency

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The system implements a feedback mechanism where radiologists rate image quality, and this feedback is used to automatically update acquisition parameters across distributed sites. The feedback loop ensures continuous improvement and synchronization of parameters without manual intervention.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs preliminary actions by automatically selecting and configuring acquisition parameters before image acquisition based on feedback from radiologists. This eliminates the need for manual parameter selection and ensures up-to-date parameters are used across all sites.

Inventive Principle:

Principle #10Preliminary action

2Extent of automation

If quantitative image quality measurement techniques are used, then automatic verification of image quality is enabled, but not all aspects of image quality are captured and sufficient differentiation is not achieved

Engineering Contradiction:

Improveautomatic quality verificationVSAvoidimage quality assessment accuracy

Core Design Contradiction:

Extent of automationVSMeasurement precision

Solution Approach 1:

The system introduces radiologists as intermediaries who provide subjective quality assessments. Their feedback serves as a mediator between automatic quantitative measurements and final quality determination, capturing aspects that purely quantitative methods miss.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system merges quantitative automated measurements with qualitative radiologist feedback to create a comprehensive image quality assessment. This combination captures both objective metrics and subjective aspects of image quality.

Inventive Principle:

Principle #5Merging (Combining)

3Adaptability or versatility

If acquisition parameters are stored locally at each imaging device, then each site has independent access to parameters, but inconsistencies occur across sites and obsolete protocols may be applied

Engineering Contradiction:

Improvelocal parameter accessVSAvoidparameter synchronization

Core Design Contradiction:

Adaptability or versatilityVSStability of the object's composition

Solution Approach 1:

The system uses feedback from radiologists to automatically update acquisition parameters stored locally at each imaging device. This feedback mechanism ensures all sites receive updated parameters simultaneously, maintaining synchronization while allowing local access.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system creates a universal parameter set that can be applied across all distributed imaging sites. The centralized feedback-driven parameter selection ensures consistency while maintaining local accessibility and adaptability to specific site needs.

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Adaptability or versatility

If technicians adjust acquisition parameters verbally with radiologists, then personalized parameters can be provided, but inappropriate adjustments may occur and time is lost

Engineering Contradiction:

Improvepersonalized parameter adjustmentVSAvoidparameter adjustment time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system performs preliminary parameter selection and configuration automatically based on radiologist feedback from previous examinations. This eliminates the need for time-consuming verbal adjustments while maintaining personalized parameters for each radiologist.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system enables self-service by automatically selecting and configuring acquisition parameters based on stored radiologist preferences and feedback. This eliminates the need for technician-radiologist communication while maintaining personalized settings.

Inventive Principle:

Principle #25Self-service

Data Source

PatentEP3680912B1Technique for performing a quality assessment for a medical image

Publication Date: 2022.06.29 MEDNEO

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AI summary

A technique for performing a feedback-based quality assessment for a medical image acquired by a medical imaging device is disclosed. A method implementation of the technique comprises determining (S108) a level of image quality for the acquired medical image using an assessment component configured to assess image quality levels based on feedback of physicians collected for previously acquired medical images.