Myung Hye Cho

A flat-panel detector based micro-CT system: performance evaluation for small-animal imaging

A dedicated small-animal x-ray micro computed tomography (micro-CT) system has been developed to screen laboratory small animals such as mice and rats. The micro-CT system consists of an indirect-detection flat-panel x-ray detector with a field-of-view of 120 x 120 mm2, a microfocus x-ray source, a rotational subject holder and a parallel data processing system. The flat-panel detector is based on a matrix-addressed photodiode array fabricated by a CMOS (complementary metal-oxide semiconductor) process coupled to a CsI:T1 (thallium-doped caesium iodide) scintillator as an x-ray-to-light converter. Principal imaging performances of the micro-CT system have been evaluated in terms of image uniformity, voxel noise and spatial resolution. It has been found that the image non-uniformity mainly comes from the structural non-uniform sensitivity pattern of the flat-panel detector and the voxel noise is about 48 CT numbers at the voxel size of 100 x 100 x 200 microm3 and the air kerma of 286 mGy. When the magnification ratio is 2, the spatial resolution of the micro-CT system is about 14 1p/mm (line pairs per millimetre) that is almost determined by the flat-panel detector showing about 7 1p/mm resolving power. Through low-contrast phantom imaging studies, the minimum resolvable contrast has been found to be less than 36 CT numbers at the air kerma of 95 mGy. Some laboratory rat imaging results are presented.

X-ray micro-tomography system for small-animal imaging with zoom-in imaging capability

Since a micro-tomography system capable of microm-resolution imaging cannot be used for whole-body imaging of a small laboratory animal without sacrificing its spatial resolution, it is desirable for a micro-tomography system to have local imaging capability. In this paper, we introduce an x-ray micro-tomography system capable of high-resolution imaging of a local region inside a small animal. By combining two kinds of projection data, one from a full field-of-view (FOV) scan of the whole body and the other from a limited FOV scan of the region of interest (ROI), we have obtained zoomed-in images of the ROI without any contrast anomalies commonly appearing in conventional local tomography. For experimental verification of the zoom-in imaging capability, we have integrated a micro-tomography system using a microfocus x-ray source, a 1248 x 1248 flat-panel x-ray detector, and a precision scan mechanism. The mismatches between the two projection data caused by misalignments of the scan mechanism have been estimated with a calibration phantom, and the mismatch effects have been compensated in the image reconstruction procedure. Zoom-in imaging results of bony tissues with a spatial resolution of 10 lp mm(-1) suggest that zoom-in micro-tomography can be greatly used for high-resolution imaging of a local region in small-animal studies.

Methods and evaluations of MRI content-adaptive finite element mesh generation for bioelectromagnetic problems

In studying bioelectromagnetic problems, finite element analysis (FEA) offers several advantages over conventional methods such as the boundary element method. It allows truly volumetric analysis and incorporation of material properties such as anisotropic conductivity. For FEA, mesh generation is the first critical requirement and there exist many different approaches. However, conventional approaches offered by commercial packages and various algorithms do not generate content-adaptive meshes (cMeshes), resulting in numerous nodes and elements in modelling the conducting domain, and thereby increasing computational load and demand. In this work, we present efficient content-adaptive mesh generation schemes for complex biological volumes of MR images. The presented methodology is fully automatic and generates FE meshes that are adaptive to the geometrical contents of MR images, allowing optimal representation of conducting domain for FEA. We have also evaluated the effect of cMeshes on FEA in three dimensions by comparing the forward solutions from various cMesh head models to the solutions from the reference FE head model in which fine and equidistant FEs constitute the model. The results show that there is a significant gain in computation time with minor loss in numerical accuracy. We believe that cMeshes should be useful in the FEA of bioelectromagnetic problems.

Trabecular thickness measurement in cancellous bones: postmortem rat studies with the zoom-in micro-tomography technique.

Using the cross-sectional images taken with the zoom-in micro-tomography technique, we measured trabecular thicknesses of femur bones in postmortem rats. Since the zoom-in micro-tomography technique is capable of high resolution imaging of a small local region inside a large subject, we were able to measure the trabecular thickness without extracting bone samples from the rats. For the zoom-in micro-tomography, we used a micro-tomography system consisting of a micro-focus x-ray source, a 1248 x 1248 flat-panel x-ray detector and a precision scan mechanism. To compensate for the limited spatial resolution in the zoom-in micro-tomography images, we used the fuzzy distance transform for the calculation of the trabecular thickness. To validate the trabecular thickness measurement with the zoom-in micro-tomography images, we compared the measurement results with those obtained from the conventional micro-tomography images of the extracted bone samples. The difference between the two types of measurement results was less than 2.5%.

Influence of White Matter Anisotropy on the Effects of Transcranial Direct Current Stimulation: A Finite Element Study

Although the use of transcranial direct current stimulation (tDCS), a noninvasive brain stimulation technique, has become popular in cognitive neuroscience research and clinical applications, there still exists limited knowledge on how to optimally use tDCS for the brain stimulation. To understand the underlying principles and effects of tDCS, finite element analysis (FEA) has been successfully applied due to its truly volumetric analysis and capability of incorporating the anisotropic tissue property. However, there are still many factors to be considered in stimulation: the influence of the white matter (WM) anisotropy is one of them which has not been considered in tDCS. In this study, we have examined the influence of the WM anisotropic conductivities on tDCS via high-resolution FE head models of the whole head. The effects of the WM anisotropy has been assessed by comparing the current density maps computed from the anisotropic FE model against those of the isotropic model using the similarity measures. The results show that there are significant differences caused by the tissue anisotropy, indicating that the anisotropic electrical conductivity is one of the critical factors to be considered during tDCS for accurate and effective stimulation of the brain.

Development and Characterization of a Flat-Panel Detector-Based Microtomography System

In this paper, we describe the development and performance evaluation of a 3-dimentional (3-D) high-resolution x-ray microtomography (micro-CT) system. Unlike a conventional micro-CT, the developed system uses a flat-panel detector as a digital x-ray imager. The detector is a CsI:Tl (thallium-doped cesium iodide) scintillator coupled to an active-matrix photodiode array with a pixel pitch of 50 [μm]. Without geometric magnification, the spatial resolution of the detector is 7 [lp/mm] at 10 [%] of MTF (modulation-transfer function). The overall efficiency of the detector for the input x-ray signal-to-noise ratio (SNR) has been measured to be about 50 [%] with the x-ray source operating at 60 [kVp] and 1-mm-thick Al filtration. For fast 3-D cone-beam image reconstruction, the Feldkamp algorithm has been realized in a distributed parallel processing system composed of multiple personal computers. The signal and noise properties in tomograms have been measured with quantitative phantoms and the measurement results are found to conform well to the theoretical models. From the measurements, it has been also found that the spatial resolution in a tomogram is almost determined by the detector resolving power. Some high-resolution imaging results are shown to demonstrate the capability of the developed system in bio-medical and industrial applications.

Performance evaluation of a flat-panel detector-based microtomography system for small-animal imaging

We have applied a flat-panel detector to an X-ray cone-beam micro computed tomography (micro-CT) for small-animal imaging. The flat-panel detector consists of an active matrix of transistors and photodiodes with a pixel pitch of 50 /spl mu/m and a thallium-doped cesium iodide (CsI:Tl) scintillator as an X-ray-to-light conversion layer. The detector was fabricated with a CMOS (complementary metal-oxide-semiconductor) technology capable of a sub-micrometer design line width, hence, it has a pixel fill-factor as high as /spl sim/80%. In addition, the detector has a very fast response characteristic with an image lag being less than 0.3% in the frame integration time of 5 s. Characterization of the CMOS flat-panel detector has been performed in terms of modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE). Tomographic imaging performances of the micro-CT system, such as, voxel noise, contrast-to-noise ratio (CNR), and spatial resolution, have also been evaluated by using various quantitative phantoms. Experimental results of euthanized laboratory rat imaging suggest that the micro-CT system employing a CMOS flat-panel detector can be greatly used in small-animal imaging.

Content-Adaptive Finite Element Mesh Generation of 3-D Complex MR Volumes for Bioelectromagnetic Problems

In studying bioelectromagnetic problems, finite element method offers several advantages over other conventional methods such as boundary element method. It allows truly volumetric analysis and incorporation of material properties such as anisotropy. Mesh generation is the first requirement in the finite element analysis and there are many different approaches in mesh generation. However conventional approaches offered by commercial packages and various algorithms do not generate content-adaptive meshes, resulting in numerous elements in the smaller volume regions, thereby increasing computational load and demand. In this work, we present an improved content-adaptive mesh generation scheme that is efficient and fast along with options to change the contents of meshes. For demonstration, mesh models of the head from a volume MRI are presented in 2-D and 3-D

Zoom-in micro tomography with the combination of full and limited field-of-view projection data

In this paper, we introduce an X-ray microtomography system capable of high-resolution zoom-in imaging of a local region inside a large object. By combining two kinds of projection data, one from the full field-of-view (FOV) scan of the whole object and the other from the limited FOV scan of the region of interest, we have obtained zoomed-in images of the region of interest. With computer simulations, we have found that the proposed zoom-in imaging technique has superb spatial resolution, comparable to that of local tomography, without any contrast anomalies commonly appearing in conventional local tomography. To verify the zoom-in imaging capability experimentally, we have integrated a micro tomography system using a micro-focus X-ray source, a flat-panel CMOS X-ray detector with the matrix size of 1248times1248, and a precision scan mechanism. The mismatches between the two projection data caused by misalignments of the scan mechanism have been estimated with a calibration phantom and the mismatch effects have been compensated in the image reconstruction procedure. Zoom-in imaging results of bony tissues with the spatial resolution of 20 mum suggest that zoom-in microtomography can be greatly used for high resolution imaging of a local region in small animal imaging studies

A Ring Artifact Correction Method: Validation by Micro-CT Imaging with Flat-Panel Detectors and a 2D Photon-Counting Detector

We introduce an efficient ring artifact correction method for a cone-beam computed tomography (CT). In the first step, we correct the defective pixels whose values are close to zero or saturated in the projection domain. In the second step, we compute the mean value at each detector element along the view angle in the sinogram to obtain the one-dimensional (1D) mean vector, and we then compute the 1D correction vector by taking inverse of the mean vector. We multiply the correction vector with the sinogram row by row over all view angles. In the third step, we apply a Gaussian filter on the difference image between the original CT image and the corrected CT image obtained in the previous step. The filtered difference image is added to the corrected CT image to compensate the possible contrast anomaly that may appear due to the contrast change in the sinogram after removing stripe artifacts. We applied the proposed method to the projection data acquired by two flat-panel detectors (FPDs) and a silicon-based photon-counting X-ray detector (PCXD). Micro-CT imaging experiments of phantoms and a small animal have shown that the proposed method can greatly reduce ring artifacts regardless of detector types. Despite the great reduction of ring artifacts, the proposed method does not compromise the original spatial resolution and contrast.