• Journal of Radiation Protection and Research
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• v.44 no.4
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• pp.149-155
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• 2019

Background: Magnetic resonance (MR) image guided radiation therapy system, enables real time MR guided radiotherapy (RT) without additional radiation exposure to patients during treatment. However, MR image lacks electron density information required for dose calculation. Image fusion algorithm with deformable registration between MR and computed tomography (CT) was developed to solve this issue. However, delivered dose may be different due to volumetric changes during image registration process. In this respect, synthetic CT generated from the MR image would provide more accurate information required for the real time RT. Materials and Methods: We analyzed 1,209 MR images from 16 patients who underwent MR guided RT. Structures were divided into five tissue types, air, lung, fat, soft tissue and bone, according to the Hounsfield unit of deformed CT. Using the deep learning model (U-NET model), synthetic CT images were generated from the MR images acquired during RT. This synthetic CT images were compared to deformed CT generated using the deformable registration. Pixel-to-pixel match was conducted to compare the synthetic and deformed CT images. Results and Discussion: In two test image sets, average pixel match rate per section was more than 70% (67.9 to 80.3% and 60.1 to 79%; synthetic CT pixel/deformed planning CT pixel) and the average pixel match rate in the entire patient image set was 69.8%. Conclusion: The synthetic CT generated from the MR images were comparable to deformed CT, suggesting possible use for real time RT. Deep learning model may further improve match rate of synthetic CT with larger MR imaging data.

• Progress in Medical Physics
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• v.33 no.4
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• pp.142-149
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• 2022

Purpose: This study seeks to compare the dosimetric parameters of the bulk electron density (ED) approach and synthetic computed tomography (CT) image in terms of position variation of the air cavity in magnetic resonance-guided radiotherapy (MRgRT) for patients with pancreatic cancer. Methods: This study included nine patients that previously received MRgRT and their simulation CT and magnetic resonance (MR) images were collected. Air cavities were manually delineated on simulation CT and MR images in the treatment planning system for each patient. The synthetic CT images were generated using the deep learning model trained in a prior study. Two more plans with identical beam parameters were recalculated with ED maps that were either manually overridden by the cavities or derived from the synthetic CT. Dose calculation accuracy was explored in terms of dose-volume histogram parameters and gamma analysis. Results: The D_95% averages were 48.80 Gy, 48.50 Gy, and 48.23 Gy for the original, manually assigned, and synthetic CT-based dose distributions, respectively. The greatest deviation was observed for one patient, whose D_95% to synthetic CT was 1.84 Gy higher than the original plan. Conclusions: The variation of the air cavity position in the gastrointestinal area affects the treatment dose calculation. Synthetic CT-based ED modification would be a significant option for shortening the time-consuming process and improving MRgRT treatment accuracy.

• Progress in Medical Physics
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• v.32 no.4
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• pp.172-178
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• 2021

Purpose: This study aimed to develop a deep learning architecture combining two task models to generate synthetic computed tomography (sCT) images from low-tesla magnetic resonance (MR) images to improve metallic marker visibility. Methods: Twenty-three patients with cervical cancer treated with intracavitary radiotherapy (ICR) were retrospectively enrolled, and images were acquired using both a computed tomography (CT) scanner and a low-tesla MR machine. The CT images were aligned to the corresponding MR images using a deformable registration, and the metallic dummy source markers were delineated using threshold-based segmentation followed by manual modification. The deformed CT (dCT), MR, and segmentation mask pairs were used for training and testing. The sCT generation model has a cascaded three-dimensional (3D) U-Net-based architecture that converts MR images to CT images and segments the metallic marker. The performance of the model was evaluated with intensity-based comparison metrics. Results: The proposed model with segmentation loss outperformed the 3D U-Net in terms of errors between the sCT and dCT. The structural similarity score difference was not significant. Conclusions: Our study shows the two-task-based deep learning models for generating the sCT images using low-tesla MR images for 3D ICR. This approach will be useful to the MR-only workflow in high-dose-rate brachytherapy.

• Journal of Korean Neurosurgical Society
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• v.63 no.3
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• pp.386-396
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• 2020

Objective : To generate synthetic spine magnetic resonance (MR) images from spine computed tomography (CT) using generative adversarial networks (GANs), as well as to determine the similarities between synthesized and real MR images. Methods : GANs were trained to transform spine CT image slices into spine magnetic resonance T2 weighted (MRT2) axial image slices by combining adversarial loss and voxel-wise loss. Experiments were performed using 280 pairs of lumbar spine CT scans and MRT2 images. The MRT2 images were then synthesized from 15 other spine CT scans. To evaluate whether the synthetic MR images were realistic, two radiologists, two spine surgeons, and two residents blindly classified the real and synthetic MRT2 images. Two experienced radiologists then evaluated the similarities between subdivisions of the real and synthetic MRT2 images. Quantitative analysis of the synthetic MRT2 images was performed using the mean absolute error (MAE) and peak signal-to-noise ratio (PSNR). Results : The mean overall similarity of the synthetic MRT2 images evaluated by radiologists was 80.2%. In the blind classification of the real MRT2 images, the failure rate ranged from 0% to 40%. The MAE value of each image ranged from 13.75 to 34.24 pixels (mean, 21.19 pixels), and the PSNR of each image ranged from 61.96 to 68.16 dB (mean, 64.92 dB). Conclusion : This was the first study to apply GANs to synthesize spine MR images from CT images. Despite the small dataset of 280 pairs, the synthetic MR images were relatively well implemented. Synthesis of medical images using GANs is a new paradigm of artificial intelligence application in medical imaging. We expect that synthesis of MR images from spine CT images using GANs will improve the diagnostic usefulness of CT. To better inform the clinical applications of this technique, further studies are needed involving a large dataset, a variety of pathologies, and other MR sequence of the lumbar spine.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.30 no.1
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• pp.21-26
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• 2020

This article reports the result on the spectroscopic analysis of the three Lightbox CVD-grown diamonds. Lightbox Jewelry, a De Beers company, has begun selling CVD laboratory-grown diamonds since September 2018. Recently, we had the opportunity to examine three Lightbox's pendant necklaces. The 0.25 ct, 0.25 ct, and 0.26 ct round brilliant were graded as "H" near colorless, Fancy Vivid orangy pink, and Fancy Vivid blue with cut grades of excellent, respectively. The laser-inscribed Lightbox logo under the table, large enough to be easily visible with a microscope. Based on the spectroscopic techniques, for near colorless sample was not subjected to post-growth HPHT processing to improve its color. For pink sample, optical centers at H3, 3H, 594 nm, NV, and GR1 were recorded. It was speculated that the pink sample have been received irradiation and annealing. In addition, the blue CVD synthetic sample was concluded to be irradiated without annealing.

• Journal of Veterinary Clinics
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• v.30 no.4
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• pp.268-272
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• 2013

The purpose of this study was to assess the effects of reconstruction kernel, and slice thickness on the accuracy of spiral CT-based volume assessment over a range of object sizes typical of synthetic simulated tumor. Spiral CT scanning was performed at various reconstruction kernels (soft tissue, standard, bone), and slice thickness (1, 2, 3 mm) using a phantom made of gelatin and 10 synthetic simulated tumors of different sizes (diameter 3.0-12.0 mm). Three-dimensional volume assessments were obtained using an automated software tool. Results were compared with the reference volume by calculating the percentage error. Statistical analysis was performed using ANOVA and setting statistical significance at P < 0.05. In general, smaller slice thickness and larger sphere diameters produced more accurate volume assessment than larger slice thickness and smaller sphere diameter. The measured volumes were larger than the actual volumes by a common factor depending on slice thickness; in 100HU simulated tumors that had statistically significant, 1 mm slice thickness produced on average 27.41%, 2 mm slice thickness produced 45.61%, 3 mm slice thickness produced 93.36% overestimates of volume. However, there was no statistically significant difference in volume error for spiral CT scans taken with techniques where only reconstruction kernel was changed. These results supported that synthetic simulated tumor size, slice thickness were significant parameters in determining volume measurement errors. For an accurate volumetric measurement of an object, it is critical to select an appropriate slice thickness and to consider the size of an object.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.27 no.4
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• pp.149-153
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• 2017

Recently, significant amounts of gem-quality colorless HPHT synthetic melee diamond have produced for the jewelry industry. Consequently, there have been reports of cases of fraud in the world diamond business. For example, intentionally selling synthetic diamond as natural diamond or intentionally mixing a natural diamond parcel with a synthetic. As a result, the separation of natural from synthetic melee diamonds has become increasingly critical. At present, 10,000 cubic hinge presses are used for the production of synthetic diamond in China. From among these, reportedly 1,000 presses are used for gem-quality diamond production. One press can produce up to 10ct melee-size diamonds in 24 hours. Randomly occurring pinpoint or flux-metal inclusions are diagnostic identification clues. However, some synthetic diamonds require advanced laboratory method for identification. In order to ensure consumer confidence, it is essential to screen melees so as to distinguish all synthetic goods.

• Radiation Oncology Journal
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• v.38 no.1
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• pp.52-59
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• 2020

Purpose: To evaluate and compare the feasibilities of magnetic resonance (MR) image-based planning using synthetic computed tomography (sCT) versus CT (pCT)-based planning in helical tomotherapy for prostate cancer. Materials and Methods: A retrospective evaluation was performed in 16 patients with prostate cancer who had been treated with helical tomotherapy. MR images were acquired using a dedicated therapy sequence; sCT images were generated using magnetic resonance for calculating attenuation (MRCAT). The three-dimensional dose distribution according to sCT was recalculated using a previously optimized plan and was compared with the doses calculated using pCT. Results: The mean planning target volume doses calculated by sCT and pCT differed by 0.65% ± 1.11% (p = 0.03). Three-dimensional gamma analysis at a 2%/2 mm dose difference/distance to agreement yielded a pass rate of 0.976 (range, 0.658 to 0.986). Conclusion: The dose distribution results obtained using tomotherapy from MR-only simulations were in good agreement with the dose distribution results from simulation CT, with mean dose differences of less than 1% for target volume and normal organs in patients with prostate cancer.

• Journal of Korean Neurosurgical Society
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• v.61 no.6
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• pp.737-746
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• 2018

Objective : The purpose of this study was to compare the cosmetic outcome and complications after cranioplasty (CP) due to three different implant materials, and analyze the mean implant survival and cumulative survival rate based on these results. Methods : We reviewed 108 patients retrospectively who underwent CP between January 2014 and November 2016. Autologous bone (AB; 45 patients) and synthetic materials with porous polyethylene (PP; 32 patients) and custom-made 3-dimensional printed titanium mesh (CT; 31 patients) were used as implants. Results : Regardless of implanted materials, more than 89.8% of the CP patients were satisfied with the cosmetic outcome. No statistically significant difference was observed among the three groups. The overall postoperative complication rates of each group were 31.1% in the AB group, 15.6% in the PP group and 3.2% in the CT group. The CT group showed lower complication rates compared with AB and PP groups (${\chi}^2$-test : AB vs. PP, p=0.34; AB vs. CT, p=0.00; PP vs. CT, p=0.03). The AB and PP groups demonstrated a higher post-CP infection rate (11.1% and 6.3%) than the CT group (3.2%). However, no significant difference in the incidence of post-CP infection was observed among the three groups. The PP and CT groups demonstrated a higher mean implant survival time and cumulative survival rate than the AB group at the last follow-up (p<0.05). Conclusion : In comparison with AB and PP, cranioplasty with CT shows benefits in terms of lower post-CP complication, less intraoperative bleeding loss, shorter operation time and in-hospital stay. The PP and CT groups showed higher implant survival time and cumulative survival rate compared with the AB group.

• Journal of the Korean Institute of Telematics and Electronics
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• v.15 no.6
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• pp.8-22
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• 1978

Recently developed Computed Topography (CT) reconstruction algorithms are reviewed in a more generalized sense and a few reconstruction examples are given for illustration. The construction of an image function from the physically measured projections of some object is Discussed with reference to the least squares optimum filters, originally derived to enhance the signal-to-noise ratio in communications theory. The computerifed image processing associated with topography is generalized so as to include 3 distinct parts: the construction of an image from the projection, the restoration of a blurred, noisy image, degraded by a known space-invariant impulse response, and the further enhancement of the image, e.g. by edge sharpening. In conjunction with given versions of the popular convolution algorithm, n6t 19 be confused with filtering by a 2-diminsional convolution, we consider the conditions under which a concurrent construction, restoration, and enhancement are possible. Extensive bibliographical limits are given in the references.