Markov random field segmentation for industrial computed tomography with metal artefacts

X-ray Computed Tomography (XCT) has become an important tool for industrial measurement and quality control through its ability to measure internal structures and volumetric defects. Segmentation of constituent materials in the volume acquired through XCT is one of the most critical factors that influence its robustness and repeatability. Highly attenuating materials such as steel can introduce artefacts in CT images that adversely affect the segmentation process, and results in large errors during quantification. This paper presents a Markov Random Field (MRF) segmentation method as a suitable approach for industrial samples with metal artefacts. The advantages of employing the MRF segmentation method are shown in comparison with Otsu thresholding on CT data from two industrial objects

Implementation of a metal artifact reduction methods for small-animal CT

In the recent years, because of the constantly increasing knew discoveries in the fields of genomics and molecular biology and the development of new technologies, the use of animal models of human diseases has become more frequent. This combined with improvements in biomedical instrumentation and medical imaging has led to the development of micro CT systems enabling noninvasive investigations on animals. The work included in this thesis is framed on one of the lines of research carried out by the Biomedical Imaging and Instrumentation Group (BIIG) from the Bioengineering and Aerospace Department of Universidad Carlos III de Madrid working jointly with the Gregorio Marañón Hospital. This multidisciplinary group has developed a micro-CT system for small animals, which is used in different preclinical research lines within the group. One of these research lines focuses on the use of brain stimulation as Parkinson disease treatment. Rats have stainless electrodes implanted and fixed with screws in the lateral hypothalamus, through stereotaxic surgery. The CT subsystem of ARGUS is used then to corroborate the surgery was correct and the position of the electrodes is the right one. The presence of metallic objects creates severe streak artifacts in CT images affecting image quality and hindering the correct representation of anatomy. The beam hardening correction method, already integrated in the ARGUS system results insufficient for the correction of the artifacts derived from the presence of metals. Motivated by this context, the objective of this thesis is to implement an algorithm for metal artifact correction to be included in ARGUS. After reviewing the methods proposed in the literature the one proposed by Meyer et. al. in 2012 was implemented in MATLAB. The implemented MAR method was evaluated using simulations and real studies acquired with the ARGUS scanner, based on visual assessment, intensity profiles and mean squared error before and after the correction. The results of the evaluation showed an efficient elimination of streaks even for very strong artifact, as it is the case of gold implants. In all cases, bone edges were preserved when correcting with MAR and the metal structures are clearly delimited after correction.Ingeniería Biomédic

MR Image Based Approach for Metal Artifact Reduction in X-Ray CT

For decades, computed tomography (CT) images have been widely used to discover valuable anatomical information. Metallic implants such as dental fillings cause severe streaking artifacts which significantly degrade the quality of CT images. In this paper, we propose a new method for metal-artifact reduction using complementary magnetic resonance (MR) images. The method exploits the possibilities which arise from the use of emergent trimodality systems. The proposed algorithm corrects reconstructed CT images. The projected data which is affected by dental fillings is detected and the missing projections are replaced with data obtained from a corresponding MR image. A simulation study was conducted in order to compare the reconstructed images with images reconstructed through linear interpolation, which is a common metal-artifact reduction technique. The results show that the proposed method is successful in reducing severe metal artifacts without introducing significant amount of secondary artifacts

A Review of Automated Image Understanding within 3D Baggage Computed Tomography Security Screening

Baggage inspection is the principal safeguard against the transportation of prohibited and potentially dangerous materials at airport security checkpoints. Although traditionally performed by 2D X-ray based scanning, increasingly stringent security regulations have led to a growing demand for more advanced imaging technologies. The role of X-ray Computed Tomography is thus rapidly expanding beyond the traditional materials-based detection of explosives. The development of computer vision and image processing techniques for the automated understanding of 3D baggage-CT imagery is however, complicated by poor image resolutions, image clutter and high levels of noise and artefacts. We discuss the recent and most pertinent advancements and identify topics for future research within the challenging domain of automated image understanding for baggage security screening CT

Artifacts due to dental and maxillofacial restoration materials in cone beam computed tomography images

Over the last 20 years, three-dimensional X-ray imaging, cone beam computed tomography (CBCT), has become an important method when making the diagnoses in the dental and maxillofacial area. There has been rapid development in CBCT devices, and the image quality has improved considerably during the last two decades. Despite the many improvements in CBCT image quality, artifacts induced by dental and maxillofacial restoration materials are still a problem, especially when diagnosing the dental area. CBCT manufacturers produce artifact reduction algorithms, which are intended to decrease or remove the artifacts in the image. However, the results of the studies on artifact reduction algorithms vary and there is no final consensus, as yet, on their efficacy. The studies of the present thesis focus on the arti-facts induced by different dental restoration materials in CBCT images. Another aim was to compare how the different materials interfere with the radiologic diagnosis. The materials investigated were titanium, zirconia, composite, and fiber reinforced composite (FRC). The results showed that composites with ra-dio-opacifying BaAlSiO2 20% (weight%) or more caused artifacts in the CBCT images. Composites with BaAlSiO2 68% (weight%) or more caused artifacts with similar intensity as titanium. Titanium orbital floor implant caused artifacts in the CBCT images, whereas nonmetallic fiber reinforced composite (FRC) orbital floor implant did not cause hampering artifacts in the CBCT images. The diagnosis of apical perio-dontitis can be complicated in 70% of the CBCT images of paranasal sinuses because of the artifacts induced by dental and endodontic restorations. In the CBCT images, zirconia dental implants caused in-tense artifacts despite the artifact reduction algorithm. To conclude, different dental restoration materials cause image hampering artifacts of different intensities in CBCT images. Zirconia is especially problem-atic in CBCT images. More studies are needed on artifact reduction methods to achieve an image quality without artifacts to make the correct diagnosis. In addition, the consequences of restoration and implant material options should be considered in postoperative CBCT images

Registration-based multi-orientation tomography

We propose a combination of an experimental approach and a reconstruction technique that leads to reduction of artefacts in X-ray computer tomography of strongly attenuating objects. Through fully automatic data alignment, data generated in multiple experiments with varying object orientations are combined. Simulations and exp

Micro-Computed Tomography Semi-Empirical Beam Hardening Correction: Method And Application To Meteorites

X-ray micro-computed tomography (μCT) is able to non-destructively provide high- resolution 3D images of the internal structures of dense materials such as meteorites. The widespread availability of instruments capable of biomedical micro-computed tomography means there is ample access to scanners for the investigation of geomaterials, but the scan data can be susceptible to artifacts such as beam hardening, a consequence of high X-ray attenuation in these dense materials. A semi-empirical correction method for beam hardening and scatter that can be straightforwardly applied to available biomedical scanners is proposed and evaluated. This method uses aluminum as a single calibration material to significantly reduce or remove signal intensity errors (i.e. cupping) that occur as a result of beam hardening artifacts. X-ray transmission data are linearized using custom software. Results show that it is possible through careful analysis to determine an effective method of artifact correction for specified protocols using this implementation. Following correction and validation, this technique is applied to imaging of meteorite samples. Four meteorites are examined using μCT in combination with this processing technique: Three ordinary chondrites (Grimsby, Gao-Guenie, and Ozona) and an olivine diogenite (NWA 5480). Information from μCT is compared to that of traditional methods of analysis of meteoritic samples, and the advantages and disadvantages are discussed