Taeho Woo

Industrial x-ray inspection system with improved image characterization using blind deblurring based on compressed-sensing scheme

ABSTRACT An industrial x-ray inspection system has recently established by our group to examine large and dense objects available in industry. It consists of an industrial x-ray generator having a tube voltage of 450 kV and a focal spot size of 1 mm, a flat-panel detector having a pixel size of 200 µm and a pixel dimension of 2048 × 2048, and a mechanical support for object’s installation. For improving the image characteristics of the system, an effective blind deblurring method based on compressed-sensing scheme is reported. Blind deblurring is the image restoration by estimating the original image and the degradation mechanism using partial information on both. Compressed-sensing is a relatively new mathematical theory for solving the inverse problems. Systematic measurements were performed and the image characteristics of the restored images were quantitatively evaluated using several image-quality indicators. The results demonstrate that the deblurring method is effective for industrial x-ray inspection systems.

Feasibility Study for Improving the Image Characteristics in Digital Tomosynthesis (DTS) Using a Compressed-Sensing (Cs)-Based Pre-Deblurring Scheme

ABSTRACT Digital tomosynthesis (DTS) has been widely used in both industrial nondestructive testing and medical x-ray imaging as a popular multiplanar imaging modality. However, although it provides some of the tomographic benefits of computed tomography (CT) at reduced dose and imaging time, the image characteristics are relatively poor due to blur artifacts originated from incomplete data sampling for a limited angular range and also aspects inherent to imaging system, including finite focal spot size of the x-ray source, detector resolution, etc. In this work, in order to overcome these difficulties, we propose an intuitive method in which a compressed-sensing (CS)-based deblurring scheme is applied to the projection images before common DTS reconstruction. We implemented the proposed deblurring algorithm and performed a systematic experiment to demonstrate its viability for improving the image characteristics in DTS. According to our results, the proposed method appears to be effective for the blurring problems in DTS and seems to be promising to our ongoing application to x-ray nondestructive testing.

A new software scheme for scatter correction based on a simple radiographic scattering model

AbstractIn common radiography, image contrast is often limited due mainly to scattered x-rays and noise, decreasing the quantitative usefulness of x-ray images. Several scatter reduction methods based on software correction schemes have been extensively investigated in an attempt to overcome these difficulties, most of which are based on measurement, mathematical-physical modeling, or a combination of both. However, those methods require special equipment, system geometry, and extra manual work to measure scatter characteristics. In this study, we investigated a new software scheme for scatter correction based on a simple radiographic scattering model where the intensity of the scattered x-rays was directly estimated from a single x-ray image using a weighted l1-norm contextual regularization framework. We implemented the proposed algorithm and performed a systematic simulation and experiment to demonstrate its viability. We also conducted some clinical image studies using patient’s image data of breast and L-spine to verify the clinical effectiveness of the proposed scheme. Our results indicate that the degradation of image characteristics by scattered x-rays and noise was effectively recovered by using the proposed software scheme, thus improving radiographic visibility considerably. Graphical abstractThe schematic illustrations of scatter suppression methods by using a an antiscatter grid and b a scatter estimation algorithm.

Eliminating artifacts in single-grid phase-contrast x-ray imaging for improving image quality.

In this study, we propose a modification to a single-grid phase-contrast x-ray imaging (PCXI) system using a Fourier domain analysis technique to extract absorption, scattering, and differential phase-contrast images. The proposed modification is to rotate the x-ray grid in the image plane to achieve spectral separation between the desired information and the moiré artifact, which is introduced by the superposition of the periodic image of the grid shadow and the periodic sampling by the detector. In addition, we performed some system optimization by adjusting distances between source, object, grid, and detector to further improve image quality. This optimization aimed to increase the spectral spacing between the primary spectrum (lower frequency) and the harmonics of the spectrum (higher frequency) used to extract the various image contrasts. The table-top setup used in the experiment consisted of a focused-linear grid with a 200-lines/inch strip density, a microfocus x-ray tube with a 55-μm focal spot size, and a CMOS flat-panel detector with a 49.5-μm pixel size. The x-ray grid was rotated at 27.8° with respect to the detector and the sample was placed as close as possible to the x-ray tube. Our results indicated that the proposed method effectively eliminated the PCXI artifacts, thus improving image quality.

Image reconstruction in region-of-interest (or interior) digital tomosynthesis (DTS) based on compressed-sensing (CS)

BACKGROUND AND OBJECTIVE Digital tomosynthesis (DTS) based on filtered-backprojection (FBP) reconstruction requires a full field-of-view (FOV) scan and relatively dense projections, which results in high doses for medical imaging purposes. To overcome these difficulties, we investigated region-of-interest (ROI) or interior DTS reconstruction where the x-ray beam span covers only a small ROI containing a target area. METHODS An iterative method based on compressed-sensing (CS) scheme was compared with the FBP-based algorithm for ROI-DTS reconstruction. We implemented both algorithms and performed a systematic simulation and experiments on body and skull phantoms. The image characteristics were evaluated and compared. RESULTS The CS-based algorithm yielded much better reconstruction quality in ROI-DTS compared to the FBP-based algorithm, preserving superior image homogeneity, edge sharpening, and in-plane resolution. The image characteristics of the CS-reconstructed images in ROI-DTS were not significantly different from those in full-FOV DTS. The measured CNR value of the CS-reconstructed ROI-DTS image was about 12.3, about 1.9 times larger than that of the FBP-reconstructed ROI-DTS image. CONCLUSIONS ROI-DTS images of substantially high accuracy were obtained using the CS-based algorithm and at reduced imaging doses and less computational cost, compared to typical full-FOV DTS images. We expect that the proposed method will be useful for the development of new DTS systems.

3D reconstruction based on compressed-sensing (CS)-based framework by using a dental panoramic detector

In this work, we propose a practical method that can combine the two functionalities of dental panoramic and cone-beam CT (CBCT) features in one by using a single panoramic detector. We implemented a CS-based reconstruction algorithm for the proposed method and performed a systematic simulation to demonstrate its viability for 3D dental X-ray imaging. We successfully reconstructed volumetric images of considerably high accuracy by using a panoramic detector having an active area of 198.4 mm × 6.4 mm and evaluated the reconstruction quality as a function of the pitch (p) and the angle step (Δθ). Our simulation results indicate that the CS-based reconstruction almost completely recovered the phantom structures, as in CBCT, for p≤2.0 and θ≤6°, indicating that it seems very promising for accurate image reconstruction even for large-pitch and few-view data. We expect the proposed method to be applicable to developing a cost-effective, volumetric dental X-ray imaging system.

Investigation of reconstruction quality in digital breast tomosynthesis (DBT) based on compressed-sensing algorithm and synthesized 2D breast image

Digital breast tomosynthesis (DBT) is most commonly used in three-dimensional (3D) mammography because it provides a 3D view, so suspected tumors and massed in the breast can be detected with a higher degree of accuracy. Conventional DBT reconstruction methods are based on the filtered-backprojection (FBP) with an additional deblurring filter. However, this approach usually requires dense projection data with low noise levels for acceptable reconstruction quality. In this work, instead, we investigated a state-of-the-art image reconstruction based on the compressed-sensing (CS) theory for potential application to accurate, low-dose DBT. We implemented a CS-based algorithm as well as a FBP-based algorithm for DBT reconstruction and performed a systematic experiment to verify the usefulness of the algorithm by comparing its reconstruction quality to the FBP-based one. We successfully obtained DBT images of substantially high accuracy by using the CS-based algorithm and synthesized a 2D breast image from the CS-reconstructed DBT images, which showed heightened details retained from DBT images, indicating superior performance compared to traditional 2D breast image alone.

Vacuum assisted ion injection using deuterium gas for nano-power cell production

The vacuum-assisted Low Energy Nuclear Reaction (LENR) is investigated for power cell analysis. This nuclear reaction at room temperature conditions can give an empirical scenario. The experiment of Iwamura et al. (2002) is investigated for the theoretical analysis using a computational simulation. The vacuum can perform enough suction in order to react with the layers and the injection ions. Computer simulations using molecular behaviour show that the most probable energy for a vacancy is 20 keV. Caesium is the optimised element of the vacancy production and the vacuum is reduced linearly in the CaO compound layer. The LENR aspect is suggested using this method. If the technology is formulated theoretically, the power cell can be used for energy production.

Absorbed dose using a nanoscale ion beam for Bragg peak calibrations

The proton beam was investigated for cancer cell therapy in the pancreas. Neon ion interaction profiles were compared with the result of the proton beam, which was investigated for nanoscale ion beam interactions. Simulation for the Bragg peak calculation was performed for interactions with a human organ, the pancreas. The results show the absorbed dose and dose equivalent, which vary with the energy of ion beams. This work can give us the theoretical feasibility of constructing a heavy ion accelerator for practical purpose. Realistic treatment using human organs was calculated simply and cheaply using the computational code Stopping and Range of Ions in Matter 2008 (SRIM 2008). It is proposed to make a patient-oriented therapy, because the Bragg peak can kill the cancer cells with the minimised damage to the normal cells. Data are obtained safely, cheaply and successfully through simulation work.