Distribution Of Linear Attenuation Coefficient Research Articles

Material classification based on Dual-Energy Micro-CT images by the Gaussian mixture model.

This study aimed to implement an unsupervised classification method through the Gaussian mixture model to classify different materials using the scatter diagram of the linear attenuation coefficients acquired from dual-energy micro-CT imaging. This method estimates each cluster's distribution parameters and performs classification based on the posterior probability with a pre-determined cluster number. Our studies on dual-energy images of a phantom showed that the distribution of linear attenuation coefficient of different materials on the scatter diagram has a Gaussian distribution, and clusters can be classified using model-based clustering. The result of this classification method is related to the actual materials in the phantom, where a specific cluster represents each material. This classification method can be potentially used when the clusters are overlapped and the material is separated with high accuracy.

特異値分解による術中X線投影動画から時間濃度曲線の推定手法の開発

It is a challenge in clinical practice to estimate Time Enhancement Curves (TEC) of a Region Of Interest ( ROI ) in real time from intraoperative X-ray projection movies. In the past, TEC was estimated by obtaining the Standard Linear Attenuation Coefficient Distribution (SLACD) from a preoperative contrast-enhanced CT and combining it with an intraoperative X-ray projection movie. However, in actual clinical practice, the SLACD is often uncertain due to the unavailability of preoperative contrast-enhanced CT images and the patient's respiratory motion. We developed a method for estimating TECs at a newly defined Node Of Interest (NOIs) by applying Singular Value Decomposition ( SVD ) and prior information to intraoperative X-ray projection movies only. To validate the effectiveness of this method, twin numerical experiments were conducted using a simulated blood vessel model, and the estimation results were compared. The estimation results show that the method is able to accurately estimate the rise time of TECs and the frame of maximum concentration.

Micro‐CT study of Bomirski melanoma growing in hamster eye

PurposeThe Bomirski Hamster Melanoma (BHM) cell line has been successfully used as an eye tumor animal model in the studies on tumor vascular network, metastasis and radiation treatment. Visualization and modeling of neoangiogenesis is crucial for further ocular tumor research. This work presents visualization and image analysis of BHM eyeballs using X‐ray microtomography (micro‐CT).MethodsMicro‐CT is a nondestructive preclinical imaging method with isotropic micron resolution suitable for small ex‐vivo samples. This technique provides 3D distribution of linear attenuation coefficient realized as a stack of cross‐sectional images. The micro‐CT scanning and analysis protocol was optimized for simultaneous visualization of normal ocular tissues, and pathological vasculature of BHM. Micro‐CT image contrast was enhanced using iodine (Lugol's solution) staining technique. In this investigation the Bruker SkyScan 1272 micro‐CT system was used.ResultsThe iodine staining method provided well contrasted images presenting a globe anatomy in fine details. Advanced malignancy, with the tumor occupying the entire anterior chamber and the pathological disorganized irregular tumor vascular network was also visualized. Image analysis and processing allowed to distinguish grey level range corresponding to the particular globe and tumor structures. Quantitative analysis of BHM vessel size distribution and complexity level was performed.ConclusionsMicro‐CT enhanced with Lugol solution staining method has a great potential in preclinical eye tumor research using small animal models.

Iterative Beam Hardening Correction for Multi-Material Objects

In this paper, we propose an iterative beam hardening correction method that is applicable for the case with multiple materials. By assuming that the materials composing scanned object are known and that they are distinguishable by their linear attenuation coefficients at some given energy, the beam hardening correction problem is converted into a nonlinear system problem, which is then solved iteratively. The reconstructed image is the distribution of linear attenuation coefficient of the scanned object at a given energy. So there are no beam hardening artifacts in the image theoretically. The proposed iterative scheme combines an accurate polychromatic forward projection with a linearized backprojection. Both forward projection and backprojection have high degree of parallelism, and are suitable for acceleration on parallel systems. Numerical experiments with both simulated data and real data verifies the validity of the proposed method. The beam hardening artifacts are alleviated effectively. In addition, the proposed method has a good tolerance on the error of the estimated x-ray spectrum.

A generalized method of converting CT image to PET linear attenuation coefficient distribution in PET/CT imaging

The accuracy of attenuation correction in positron emission tomography scanners depends mainly on deriving the reliable 511-keV linear attenuation coefficient distribution in the scanned objects. In the PET/CT system, the linear attenuation distribution is usually obtained from the intensities of the CT image. However, the intensities of the CT image relate to the attenuation of photons in an energy range of 40 keV–140 keV. Before implementing PET attenuation correction, the intensities of CT images must be transformed into the PET 511-keV linear attenuation coefficients. However, the CT scan parameters can affect the effective energy of CT X-ray photons and thus affect the intensities of the CT image. Therefore, for PET/CT attenuation correction, it is crucial to determine the conversion curve with a given set of CT scan parameters and convert the CT image into a PET linear attenuation coefficient distribution. A generalized method is proposed for converting a CT image into a PET linear attenuation coefficient distribution. Instead of some parameter-dependent phantom calibration experiments, the conversion curve is calculated directly by employing the consistency conditions to yield the most consistent attenuation map with the measured PET data. The method is evaluated with phantom experiments and small animal experiments. In phantom studies, the estimated conversion curve fits the true attenuation coefficients accurately, and accurate PET attenuation maps are obtained by the estimated conversion curves and provide nearly the same correction results as the true attenuation map. In small animal studies, a more complicated attenuation distribution of the mouse is obtained successfully to remove the attenuation artifact and improve the PET image contrast efficiently.

A virtual sinogram method to reduce dental metallic implant artefacts in computed tomography-based attenuation correction for PET

Attenuation correction of PET data requires accurate determination of the attenuation map (mumap), which represents the spatial distribution of linear attenuation coefficients of different tissues at 511 keV. The presence of high-density metallic dental filling material in head and neck X-ray computed tomography (CT) scanning is known to generate streak artefacts in the resulting CT images and thus in the corresponding mumaps generated using CT-based attenuation correction. Consequently, an under/overestimation of activity concentration occurs in corresponding regions of the corrected PET images. The purpose of this study is to develop a simple yet practical approach for reduction of metallic dental implant artefacts in the generated mumaps. Currently available sinogram-based metal artefact reduction (MAR) algorithms operate directly on the raw sinograms. These usually consist of huge files stored in proprietary format not easily disclosed by the manufacturers and thus are not straightforward to read and manipulate. The proposed method uses the concept of virtual sinograms produced by forward projection of CT images in Dicom format for MAR. The projection data affected by metallic objects are detected in the sinogram space through segmentation of metallic objects in the CT image followed by forward projection of the metal-only image. Thereafter, the affected sinogram bins are replaced by interpolated values from adjacent projections using the spline interpolation technique. The algorithm was assessed using a polyethylene phantom containing materials simulating different tissues and a dedicated jaw phantom scanned before and after the insertion of metallic objects, where the corrected and noncorrected mumaps were compared with the artefact-free mumap. In addition, the Jaszczak and standard germanium phantoms including four metallic inserts were scanned on a PET/CT scanner to evaluate the impact of the MAR procedure on PET data through the comparison of uncorrected and corrected PET images to the actual activity concentrations in the phantoms. The proposed algorithm was also applied to head and neck CT images of 10 patients with metallic dental implants. The MAR method proved to be practical in a clinical setting and reduced substantially the visible metal induced artefacts. The mean relative error in regions close to metallic objects is reduced by approximately 90%. The statistical analysis of the Jaszczak and solid Ge-68 phantoms PET images did not reveal statistically significant differences between the corrected and artefact-free images (P>0.05). Moreover, the evaluation of clinical studies did not reveal statistically significant differences between the attenuation coefficients of the corrected mumaps and the expected theoretical values. The proposed MAR method provides a simple and convenient approach allowing correction for the presence of metal artefacts caused by dental implants without the need to manipulate the complex raw CT data. Further evaluation using a larger clinical PET/CT database is under way to evaluate the potential of the technique in a clinical setting.

X-ray microtomographic imaging and analysis for basic research

For research facilities with access to synchrotron X-ray sources, X-ray absorption microtomography (XMT) has evolved from an experimental imaging method to a specialized, if not yet routine, microscopy for imaging the three-dimensional (3D) distribution of linear attenuation coefficients and, in some cases, elemental concentration with micron spatial resolution. Recent advances in source and detector design have produced conventional X-ray source instruments with comparable spatial resolution but with lower throughput and without element specific imaging. Both classes of instrument produce 3D images for analysis. We discuss an integrated approach for the implementation of analytical XMT to support basic research into the structure-property relationships of a variety of materials. The essential components include instrumentation for collecting quantitative 3D images, a 3D image processing environment to address questions as to the quantity, composition, geometry, and relationships among the features in one or more images, and visualization to provide insight and communicate results. We give examples of image analysis of resolved and unresolved pore spaces of sandstones.

Longitudinal Study of the Three-Dimensional Development of Subsurface Enamel Lesions during in vitro Demineralisation

A longitudinal study was made of the 3D development of subsurface enamel lesions in whole human molars. X-ray microtomography (XMT) was used to measure the 3D distribution of linear attenuation coefficients in the tissue at 8–15 stages during cumulative times of 36–107 days demineralisation through ∼1-mm-wide windows. Although lesion morphology was consistent with preferential anisotropic dissolution parallel to enamel prisms at the advancing front, detail (at a scale of ∼100 µm) varied in relation to exposed surface sites separated by <1 mm. The distribution of mineral in the most superficial region varied across the exposed face of each lesion. Within lesions, localised foci of low mineral concentration (at a scale of ∼200 µm) retained their general form through successive stages of demineralisation before coalescing. The most advanced regions within a lesion seemed to correspond with surface regions with lowest mineral concentration. These findings indicate that local variations in fractional pore volume of partially demineralised enamel influence the subsequent spatial development of lesions.

Radiography of nonaxisymmetric objects: An onion-peeling inversion method

An onion-peeling method for obtaining the linear attenuation coefficient distribution within a body from a single radiographic projection is presented. Unlike previous methods, which are applicable only to axi- or centrosymmetric objects, ours requires only mirror symmetry relative to the plane of the radiograph. An example of the use of the method is presented and discussed.

Evaluation of a Combined Transmission and Scattering Approach to Composition Imaging of Industrial Samples

Composition imaging of industrial samples has been reported using dual energy and multiple energy transmission computed tomography [1,2]. The simplest approach utilizes monoenergetic sources to obtain tomographs of a sample at two different energies. Each tomograph represents the linear attenuation coefficient distribution of the sample at the given source energy.

A tomographic gamma-ray scanner for industrial applications

An experimental computerised tomographic (CT) gamma-ray scanner is being developed for the non-destructive testing of industrial objects. A micro-computer controlled traversing system steps the test object across a collimated gamma-ray beam the transmitted intensity of which is measured by a NaI(Tl) detector for a large number of beam paths both through the object and the surrounding air. These data are used to reconstruct an image of the scanned section in terms of a two-dimensional distribution of linear attenuation coefficients at the gamma-ray energy used. A 100 mCi 241Am source of 59.6 keV gamma-rays has been used initially in order to compare the performance with medical CT X-ray scanners.