Automated Image Registration Accuracy Without Manual Landmarks

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Solution Overview

Problem

Current image registration methods rely on manual landmarking or proxy-based accuracy metrics, which are not accurate and can lead to perverse similarity results, lacking a comprehensive, automated method to integrate, analyze, and visualize registration quality without landmarks.

Innovation Solution

A method and system that automatically determine registration accuracy by identifying image elements in a shared background coordinate space, calculating distances between corresponding points, and minimizing differences to assess true registration quality without manual intervention.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If landmark-free methods are used to assess registration accuracy, then manual intervention is eliminated and automation is improved, but measurement precision deteriorates because proxy metrics do not calculate distance between truly corresponding points

Engineering Contradiction:

Improveautomation of registration accuracy assessmentVSAvoidaccuracy of registration quality measurement

Core Design Contradiction:

Extent of automationVSMeasurement precision

Solution Approach 1:

The system uses the images themselves to automatically determine correspondence and calculate registration accuracy. By scanning images sequentially and using background coordinate systems to identify intended target points, the method enables the images to self-assess their registration quality without external landmarks or proxy metrics, resolving the contradiction between automation and measurement precision

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Background coordinate systems serve as an intermediary mechanism that bridges the gap between image coordinate systems. These background coordinate systems provide a reference framework that allows automatic determination of corresponding points and calculation of distances, enabling precise accuracy assessment without manual landmarking while maintaining full automation

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If image similarity metrics are used as proxies for accuracy, then automated analysis is enabled, but measurement precision deteriorates because these metrics do not compare points with meaningful correspondence

Engineering Contradiction:

Improveautomated image analysis capabilityVSAvoidaccuracy of registration quality measurement

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The method segments the image analysis process into distinct steps: scanning images sequentially to identify elements, determining background coordinate systems, calculating distances between corresponding points, and computing accuracy metrics. This segmentation allows automated processing while ensuring that only points with meaningful correspondence are compared, maintaining measurement precision

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The invention replaces the mechanical process of manual landmarking with an automated scanning and calculation system. By using sequential scanning of image units and mathematical calculation of distances in background coordinate spaces, the system achieves both automation and precision without relying on subjective manual intervention or imprecise proxy metrics

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If manual landmarking is used to assess registration accuracy, then measurement precision is maintained, but productivity deteriorates due to manual intervention requirements

Engineering Contradiction:

Improveaccuracy of registration quality measurementVSAvoidthroughput of registration analysis

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system eliminates the need for manual landmarking by enabling the images to automatically determine their own correspondence and accuracy. The sequential scanning and background coordinate system approach allows the computer to perform what would otherwise require expert manual annotation, dramatically increasing productivity while maintaining the precision of traditional landmark-based methods

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The method performs preliminary actions by sequentially scanning images to identify all image elements and establishing background coordinate systems before calculating registration accuracy. This preliminary processing enables automated, high-speed analysis while ensuring that all necessary correspondence information is captured, achieving both high productivity and measurement precision

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250259318A1Method and system for automatic determination of registration accuracy

Publication Date: 2025.08.14 NEUROSIMPLICITY LLC

AI summary

Automatic determination of registration accuracy between a first image of a first object and a second image of the first object. Identifying a first image element in the first object by scanning the first image sequentially by image unit, and identifying a second image element in the first object by scanning the second image sequentially by the image unit. Registering the first image element to the second image element in a shared background coordinate space. Determining an accuracy of the registering by relating the first image element and the second image element to the shared background coordinate space, calculating a first distance between the first image element and a nearest point in the shared background coordinate space, and calculating a second distance between the second image element and the nearest point in the shared background coordinate space. Calculating a difference between the first distance and the second distance.