Blood Vessel Frame Selection in Medical Imaging Using Intensity Stability

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Solution Overview

Problem

Existing methods for selecting an optimal frame from medical images with contrast agents are prone to errors, often misidentifying frames due to foreign materials or insufficient contrast agent presence, leading to unsuitable frames being chosen for analysis.

Innovation Solution

A method involving a machine learning model to mask blood vessel regions, calculate intensity, determine a frame section with stable intensity distribution, and select a frame image based on predefined thresholds and electrocardiogram data to ensure optimal frame selection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Illumination intensity

If the frame image with the highest intensity of contrast agent is selected, then the contrast agent visibility is improved, but the reliability of frame selection deteriorates due to misidentification of foreign materials or insufficient contrast agent presence

Engineering Contradiction:

Improvecontrast agent intensityVSAvoidframe selection reliability

Core Design Contradiction:

Illumination intensityVSReliability

Solution Approach 1:

The patent changes the selection parameter from simple intensity threshold to a combination of intensity distribution analysis and temporal stability criteria. By analyzing the distribution pattern and temporal consistency of intensity values across multiple frames, the system identifies frames where contrast agent is truly present and stable, rather than just selecting the frame with maximum intensity which may contain foreign materials or artifacts.

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If manual frame selection is performed by medical staff, then the diagnostic accuracy is improved, but the time consumption and operational complexity increase

Engineering Contradiction:

Improvediagnostic accuracyVSAvoidframe selection time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system implements self-service by automatically performing frame selection based on objective intensity distribution criteria. The algorithm independently analyzes intensity values across frames, identifies stable contrast agent presence patterns, and selects optimal frames without requiring manual medical staff intervention, thereby eliminating time loss while maintaining diagnostic accuracy through automated objective selection.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical manual selection process with an automated computational system. Instead of medical staff visually examining and selecting frames, the system uses algorithmic analysis of intensity distributions and temporal patterns to automatically identify and select optimal frames, substituting human manual operation with automated image processing and decision-making algorithms.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Ease of operation

If simple intensity thresholding is used for frame selection, then the ease of operation is improved, but the measurement precision deteriorates due to error in identifying suitable frames

Engineering Contradiction:

Improveselection method simplicityVSAvoidframe identification accuracy

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent segments the frame selection process into multiple analytical stages: intensity calculation for each frame, distribution pattern analysis, temporal stability assessment, and final selection. This segmentation allows the system to maintain simplicity in operation while improving precision by systematically evaluating multiple criteria across different stages rather than relying on a single simple threshold.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system introduces intermediary analysis steps between simple intensity measurement and final frame selection. These intermediaries include distribution pattern analysis and temporal stability assessment that mediate between the simple input (intensity values) and the final decision (frame selection), thereby improving identification accuracy while maintaining operational simplicity through automated multi-criteria evaluation.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS12383217B2Method and system for selecting an optimal frame using distribution of intensity for each frame image of medical imaging

Publication Date: 2025.08.12 MEDIPIXEL INC

AI summary

Provided is a method for selecting an optimal frame using a distribution of intensities for each frame image of a medical image, which is performed by one or more processors of an information processing system. The method includes receiving a medical image associated with a blood vessel injected with a contrast agent, the medical image including a plurality of frame images, calculating an intensity for each of the plurality of frame images of the medical image, determining, based on a distribution of a plurality of intensities corresponding to the plurality of frame images, a frame section corresponding to a plurality of consecutive frame images of the plurality of frame images, and selecting, based on the determined frame section, a frame image from among the plurality of consecutive frame images.