A metal artifact induced HU systematic bias field modeling and correction method and system for needle intervention quantitative CT temperature measurement

By employing paired scanning and robust low-dimensional modeling in CT-guided thermal ablation, the systematic HU bias field caused by metal artifacts was corrected, solving the problem of CT temperature measurement error and achieving more accurate temperature estimation and ablation threshold determination.

CN122223178APending Publication Date: 2026-06-16FUZHOU UNIV
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Patent Information

Application Number
CN202610271264.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-06
Publication Date
2026-06-16

AI Technical Summary

Technical Problem

During CT-guided thermal ablation, the beam hardening, photon starvation, and scattering effects introduced by the metal ablation needle cause systematic HU bias field errors in temperature estimation and ablation threshold boundary shifts, which are difficult to effectively correct quantitatively using existing methods.

Method used

We employ a method of paired scanning bias field measurement, needle coordinate reparameterization, robust low-dimensional modeling, and noise threshold saliency discretization. Through voxel-by-voxel HU difference calculation, cylindrical coordinate reparameterization, multi-scale low-pass decomposition, and sparse compensation strategy, we explicitly couple the bias model to correct the CT temperature measurement link.

Benefits of technology

It reduces the interference of mid-to-low frequency systematic bias on temperature inversion, improves the quantitative consistency and interpretability of CT thermometry, and enhances the accuracy of temperature estimation and the reliability of ablation threshold determination.

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Abstract

The present application relates to a kind of metal artifact induced HU systematic bias field modeling and correction method and system for needle intervention quantitative CT temperature measurement, belong to medical image quantitative correction and thermotherapy temperature measurement technical field.The method obtains the paired CT data of needle-free and needle under the same scanning and reconstruction protocol and is registered, obtains needle caused HU bias field by voxel-by-voxel difference;Bias field is re-parameterized under needle axis reference coordinate system, and repeatable middle-low frequency systematic bias component is extracted using robust statistics aggregation and multi-scale low-pass decomposition;Combined with the influence of noise floor threshold suppression uncertain high-frequency stripe, generate bias compensation model, perform subtraction correction to subsequent needle CT data, and sparse compensation based on voxel index can be used to reduce intraoperative calculation and storage overhead.The present application can improve the stability and accuracy of quantitative CT temperature measurement in needle intervention scene, and be applicable to real-time / quasi-real-time temperature measurement and dose evaluation in the process of CT-guided thermal ablation and other interventional treatment.
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