Robotic Micro-CT Motion Correction Using LLE Geometry Estimation

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Solution Overview

Problem

Robotic-arm-based clinical micro-CT systems face challenges such as mechanical coordination errors, system misalignment, and patient movement, leading to image blurring and distortion, especially in ultrahigh resolution imaging, and interior tomography with lateral truncation artifacts.

Innovation Solution

A locally linear embedding (LLE) motion correction algorithm is employed to estimate geometry-describing parameters, including the position and orientation of the x-ray source and detector, using a sampling grid and iterative optimization to correct image artifacts, utilizing a reconstruction module for improved image data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If robotic arms are used for micro-CT imaging, then flexibility and field of view are improved, but mechanical coordination errors and system misalignment occur leading to image blurring

Engineering Contradiction:

ImproveflexibilityVSAvoidimage sharpness

Core Design Contradiction:

Adaptability or versatilityVSManufacturing precision

Solution Approach 1:

The patent implements a feedback mechanism by using detected projection data to estimate geometry-describing parameters (source position, detector position, detector orientation) and iteratively update the system model. This closed-loop feedback corrects mechanical coordination errors and misalignment in real-time, resolving the contradiction between robotic arm flexibility and image sharpness.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent replaces mechanical precision requirements with computational correction. Instead of relying solely on mechanical accuracy, the system uses LLE algorithms to computationally estimate and correct geometry parameters, substituting mechanical precision demands with information processing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Loss of energy

If interior tomography is used for oral and maxillofacial imaging, then radiation dose is reduced, but lateral truncation artifacts and data consistency issues occur

Engineering Contradiction:

Improveradiation doseVSAvoidtruncation artifacts

Core Design Contradiction:

Loss of energyVSObject-generated harmful factors

Solution Approach 1:

The patent converts the harmful effect of truncated data into a benefit by using the LLE algorithm to estimate geometry parameters from the available truncated projections. The algorithm leverages the local linear relationships in the projection data to recover accurate geometry information despite data truncation, transforming the limitation into a solvable problem.

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

Solution Approach 2:

The patent introduces geometry-describing parameters as intermediaries between the truncated projection data and the final image reconstruction. These parameters serve as a bridge that connects the incomplete data to the complete image, enabling accurate reconstruction despite lateral truncation.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Manufacturing precision

If LLE motion correction algorithm is applied, then image artifacts are reduced by over 80%, but computational complexity increases

Engineering Contradiction:

Improveimage qualityVSAvoidcomputational complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The patent segments the complex motion correction problem into distinct components: estimating source position, detector position, and detector orientation separately using LLE. This segmentation allows the algorithm to handle each geometric parameter independently, reducing the overall computational burden while maintaining high image quality.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies partial action by focusing the LLE algorithm on estimating only the critical geometry-describing parameters needed for correction, rather than processing all possible motion parameters. This selective approach achieves sufficient artifact reduction (over 80%) without the full computational cost of comprehensive motion correction.

Inventive Principle:

Principle #16Partial or excessive action

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

The LLE method effectively reduces image artifacts by over 80% and improves image sharpness and resolution, enhancing accuracy and efficiency in robotic CT imaging.

Implementation Method 1

an x-ray source coupled to a source robotic arm, an x-ray detector coupled to a detector robotic arm

Methodology Applied

Scientific EffectX-ray generation: X-Ray

Data Source

PatentUS20260060632A1Motion correction with locally linear embedding for ultrahigh resolution computed tomography

Publication Date: 2026.03.05 RENESSELAER POLYTECHNIC INST

AI summary

A CT apparatus in which the x-ray source is coupled to a source robotic arm and the detector is coupled to a detector robotic arm. A motion correction module utilizes a locally linear embedding motion correction algorithm to estimate the geometry-describing parameters associated with the positions of the source and detector and the angle of the detector. These estimates are used to reconstruct the image data and produce corrected images with fewer errors resulting from patient movement, misalignments, and coordination issues in the system.