Reducing Metal Artifacts in Computed Tomography Caused by Hip Endoprostheses Using a Physics-Based Approach

Abstract

Metal artifacts caused by hip-endoprostheses were strongly reduced. Soft tissue areas and skeletal structures surrounding the implants were well restored. The correction works by postprocessing CT datasets and it is applicable to any reconstructed image without a priori knowledge.

Improved Image Quality in Head and Neck CT Using a 3D Iterative Approach to Reduce Metal Artifact

“…More elaborate strategies include monoenergetic processing of dual-energy CT data, which works nicely for surgical plates and implants, 11,12 but its effect is limited with dental hardware. Sinogram in-painting methods 8,13,14 and iterative, 15,16 statistical, 17,18 and filtering methods 13,19 have been suggested, but for various reasons, they have not made their way into clinical practice. NMAR is an in-painting-based MAR method that is designed to reduce metal artifacts and to prevent the introduction of new artifacts by replacing raw data from the metal trace more reliably.…”

Value of monoenergetic dual-energy CT (DECT) for artefact reduction from metallic orthopedic implants in post-mortem studies

“…Various methods have been proposed for reducing metal artefacts and improving image quality in CT examinations, and these are based mainly on adjustments of CT acquisition or post-processing algorithms [12,[16][17][18][19][20][21][22][23][24][25][26].…”

Use of high resolution dual‐energy x‐ray absorptiometry‐region free analysis (DXA‐RFA) to detect local periprosthetic bone remodeling events

“…[17][18][19][20] This interface is less easily visualized using CT or MRI because of beam hardening, metal susceptibility, and magnetic field artifacts, despite recent advances in data processing and analysis using these modalities. 21 DXA-RFA also has limitations. The generation of a common template and elastic registration of all images to this template causes some image distortion, resulting in poorer precision at the individual datapoint level than that observed at ROI level with conventional DXA.…”