Correcting multi material artifacts from single material phase retrieved holo-tomograms with a simple 3D Fourier...

X-ray tomography is widely used to visualize internal structures of objects. However, when using single-material phase retrieval methods on samples containing multiple materials, artifacts can arise. These artifacts distort the reconstructed images and reduce the accuracy of the data. Prior research has shown that single-material filters are commonly used for phase retrieval, but they may fail when applied to multi-material samples. This gap motivated the development of a correction method for multi-material artifacts. No prior work had resolved how to effectively remove these artifacts without complex preprocessing. The problem is particularly relevant when the materials have different X-ray interaction properties. Existing methods often require additional calibration or specialized equipment. This paper introduces a new approach that addresses this limitation. The study focuses on samples with three distinct materials and two interfaces.

The aim of this study is to develop and demonstrate a method for correcting multi-material artifacts in X-ray tomographic data. The researchers propose using a post-processing technique based on a simple 3D Fourier method. The specific problem addressed is the appearance of artifacts when applying a single-material phase retrieval procedure to multi-material samples. The motivation is to improve the accuracy of reconstructed images without requiring complex preprocessing or specialized hardware. The method is designed for samples with three materials and two interfaces. The study tests the method on two sample types to validate its effectiveness. The goal is to provide an easy-to-apply correction method that can be used in post-processing. The researchers aim to show that this approach can be implemented with minimal additional effort.

The researchers used a single-material phase retrieval method followed by a post-processing correction technique. The correction method is based on a 3D Fourier transform approach. The method is designed for samples containing three distinct materials and two interfaces. The strongest X-ray interacting material must have sufficient absorption for segmentation. The correction is applied after phase retrieval using a grey value threshold. The method is tested on two sample types to demonstrate its effectiveness. The process involves identifying regions with high absorption and applying the correction in those areas. The approach relies on the assumption that the strongest material can be segmented using a threshold.

The correction method successfully reduces multi-material artifacts in X-ray tomographic data. The method is effective when the strongest X-ray interacting material has sufficient absorption. The correction is applied in post-processing without requiring additional calibration. The results show improved image quality for two sample types. The method is particularly useful for samples with three materials and two interfaces. The correction is based on a 3D Fourier transform approach. The method is easy to apply and does not require complex preprocessing. The results demonstrate that the correction can be implemented with minimal effort.

The authors conclude that the proposed method effectively reduces multi-material artifacts in X-ray tomographic data. The method is based on a simple 3D Fourier transform approach and is applied in post-processing. The correction is effective when the strongest X-ray interacting material has sufficient absorption. The method is tested on two sample types and shows improved image quality. The approach does not require additional calibration or specialized equipment. The correction is particularly useful for samples with three materials and two interfaces. The method is easy to apply and can be implemented with minimal effort. The results suggest that this approach can be used to improve the accuracy of reconstructed images.