• Progress in Medical Physics
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• v.21 no.1
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• pp.1-8
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• 2010

In this study, we evaluated the dose response of MAGAT (Methacrylic Acid Gelatin gel and THPC) normoxic polymer gel dosimeters based on the X-ray CT scanner. To perform this study, we determined the proper ratio of the gel composition and acquired X-ray scan parameters. MAGAT gel dosimeters were manufactured using MAA (MethacrylicAcid) and gelatin of various concentration, irradiated up to 20 Gy. We obtained the 20 CT images from the irradiated gel dosimeters by using on a Phillips Brilliance Big Bore CT scanner with the various scan parameters. This CT images were used to determine the $N_{CT}$-dose response, dose sensitivity and dose resolution As an amount of MAA and gelatin were increase, the slope and intercept were increase in each MAGAT gel dosimeter with various concentration of the $N_{CT}$-dose response curve. The dose sensitivity was $0.38{\pm}0.08$ to $0.859{\pm}0.1$ and increased were amount of the MAA was increased or the gelatin was decreased. However, the change of gelatin concentration was very small compare to MAA. The Dose resolution ($D_{\Delta}^{95%}$) varies considerably from 2.6 to 6 Gy, dependent on dose resolution and CT image noise. The slope and dose sensitivity was almost ident verywith the variation of the tube voltage, tube current and slice thickness in the dose response curve, but the noise (standard deviation of averamalg CT number) was decreased when the tube voltage, tube current and slice thickness are increase. The optimal MAGAT polymer gel dosimeter based on the CT were evaluated to determine the CT imaging scan parameters of the maximum tube voltage, tube current and slice thickness (commonly used in clinical) using the composition ratio of a 9% MAA, 8% gelatin and 83% water. This study could get proper composition ratio and scan parameter evaluating dose response of MAGAT normoxic polymer gel dosimeter using CT scanner.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.3
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• pp.235-244
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• 2000

This paper addresses a new method for constructing surface representation of 3D structures from a sequence of tomographic cross-sectional images, Firstly, we propose cell-boundary representation by transforming the cuberille space into cell space. A cell-boundary representation consists of a set of boundary cells with their 1-voxel configurations, and can compactly describe binary volumetric data. Secondly, to produce external surface from the cell-boundary representation, we define 19 modeling primitives (MP) including volumetric, planar and linear groups. Surface polygons are created from those modeling primitives using a simple table look-up operation. Comparing with previous method such as Marching Cube or PVP algorithm, our method is robust and does not make any crack in resulting surface model. Hardware implementation is expected to be easy because our algorithm is simple(scan-line), efficient and guarantees data locality in computation time.

• Journal of Biomedical Engineering Research
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• v.44 no.3
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• pp.182-189
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• 2023

CT is a medical device that acquires medical images based on Attenuation coefficient of human organs related to X-rays. In addition, using this theory, it can acquire sagittal and coronal planes and 3D images of the human body. Then, CT is essential device for universal diagnostic test. But Exposure of CT scan is so high that it is regulated and managed with special medical equipment. As the special medical equipment, CT must implement quality control. In detail of quality control, Spatial resolution of existing phantom imaging tests, Contrast resolution and clinical image evaluation are qualitative tests. These tests are not objective, so the reliability of the CT undermine trust. Therefore, by applying an artificial intelligence classification model, we wanted to confirm the possibility of quantitative evaluation of the qualitative evaluation part of the phantom test. We used intelligence classification models (VGG19, DenseNet201, EfficientNet B2, inception_resnet_v2, ResNet50V2, and Xception). And the fine-tuning process used for learning was additionally performed. As a result, in all classification models, the accuracy of spatial resolution was 0.9562 or higher, the precision was 0.9535, the recall was 1, the loss value was 0.1774, and the learning time was from a maximum of 14 minutes to a minimum of 8 minutes and 10 seconds. Through the experimental results, it was concluded that the artificial intelligence model can be applied to CT implements quality control in spatial resolution and contrast resolution.

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.1
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• pp.12-16
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• 2015

Purpose Principal component analysis (PCA) is a method often used in the neuroimagre analysis as a multivariate analysis technique for describing the structure of high dimensional correlation as the structure of lower dimensional space. PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of correlated variables into a set of values of linearly independent variables called principal components. In this study, in order to investigate the usefulness of PCA in the brain PET image analysis, we tried to analyze C[11]-PIB PET image as a representative case. Materials and Methods Nineteen subjects were included in this study (normal = 9, AD/MCI = 10). For C[11]-PIB, PET scan were acquired for 20 min starting 40 min after intravenous injection of 9.6 MBq/kg C[11]-PIB. All emission recordings were acquired with the Biograph 6 Hi-Rez (Siemens-CTI, Knoxville, TN) in three-dimensional acquisition mode. Transmission map for attenuation-correction was acquired using the CT emission scans (130 kVp, 240 mA). Standardized uptake values (SUVs) of C[11]-PIB calculated from PET/CT. In normal subjects, 3T MRI T1-weighted images were obtained to create a C[11]-PIB template. Spatial normalization and smoothing were conducted as a pre-processing for PCA using SPM8 and PCA was conducted using Matlab2012b. Results Through the PCA, we obtained linearly uncorrelated independent principal component images. Principal component images obtained through the PCA can simplify the variation of whole C[11]-PIB images into several principal components including the variation of neocortex and white matter and the variation of deep brain structure such as pons. Conclusion PCA is useful to analyze and extract the main pattern of C[11]-PIB image. PCA, as a method of multivariate analysis, might be useful for pattern recognition of neuroimages such as FDG-PET or fMRI as well as C[11]-PIB image.

• Progress in Medical Physics
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• v.26 no.1
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• pp.6-11
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• 2015

The purpose of this study was to analyze the rotational errors of roll, pitch, and yaw in the whole breast cancer treated by the three-dimensional radiation therapy (3D-CRT) using TomoDirect (TD). Twenty-patient previously treated with TD 3D-CRT was selected. We performed a retrospective clinical analysis based on 80 images of megavoltage computed tomography (MVCT) including the systematic and random variation with patient setup errors and treatment setup margin (mm). In addition, a rotational error (degree) for each patient was analyzed using the automatic image registration. The treatment margin of X, Y, and Z directions were 4.2 mm, 6.2 mm, and 6.4 mm, respectively. The mean value of the rotational error for roll, pitch, and yaw were $0.3^{\circ}$, $0.5^{\circ}$, $0.1^{\circ}$, and all of systematic and random error was within $1.0^{\circ}$. The errors of patient positioning with the Y and Z directions have generally been mainly higher than the X direction. The percentage in treatment fractions in less than $2^{\circ}$ at roll, pitch, and yaw are 95.1%, 98.8%, and 97.5%, respectively. However, the edge of upper and lower (i.e., bottom) based on the center of therapy region (point) will quite a possibility that it is expected to twist even longer as the length of treatment region. The patient-specific characters should be considered for the accuracy and reproducibility of treatment and it is necessary to confirm periodically the rotational errors, including patient repositioning and repeating MVCT scan.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.12-16
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• 2012

Purpose : In conventional PET image reconstruction, iterative reconstruction methods such as OSEM (Ordered Subsets Expectation Maximization) have now generally replaced traditional analytic methods such as filtered back-projection. This includes improvements in components of the system model geometry, fully 3D scatter and low noise randoms estimates. SharpIR algorithm is to improve PET image contrast to noise by incorporating information about the PET detector response into the 3D iterative reconstruction algorithm. The aim of this study is evaluation of SharpIR reconstruction method in PET/CT. Materials and Methods: For the measurement of detector response for the spatial resolution, a capillary tube was filled with FDG and scanned at varying distances from the iso-center (5, 10, 15, 20 cm). To measure image quality for contrast recovery, the NEMA IEC body phantom (Data Spectrum Corporation, Hillsborough, NC) with diameters of 1, 13, 17 and 22 for simulating hot and 28 and 37 mm for simulating cold lesions. A solution of 5.4 kBq/mL of $^{18}F$-FDG in water was used as a radioactive background obtaining a lesion of background ratio of 4.0. Images were reconstructed with VUE point HD and VUE point HD using SharpIR reconstruction algorithm. For the clinical evaluation, a whole body FDG scan acquired and to demonstrate contrast recovery, ROIs were drawn on a metabolic hot spot and also on a uniform region of the liver. Images were reconstructed with function of varying iteration number (1~10). Results: The result of increases axial distance from iso-center, full width at half maximum (FWHM) is also increasing in VUE point HD reconstruction image. Even showed an increasing distances constant FWHM. VUE point HD with SharpIR than VUE point HD showed improves contrast recovery in phantom and clinical study. Conclusion: By incorporating more information about the detector system response, the SharpIR algorithm improves the accuracy of underlying model used in VUE point HD. SharpIR algorithm improve spatial resolution for a line source in air, and improves contrast recovery at equivalent noise levels in phantoms and clinical studies. Therefore, SharpIR algorithm can be applied as through a longitudinal study will be useful in clinical.

• Transactions of the KSME C: Technology and Education
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• v.2 no.2
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• pp.73-80
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• 2014

Drug delivery in human upper airway was studied by the numerical simulation of oral airflow. We created an anatomically accurate upper airway model from CT scan data by using a medical image processing software (Mimics). The upper airway was composed of oral cavity, pharynx, larynx, trachea, and second generations of branches. Thin sliced CT data and meticulous refinement of model surface under the ENT doctor's advice provided more sophisticated nasal cavity models. With this 3D upper airway models, numerical simulation was conducted by ANSYS/FLUENT. The steady inspiratory airflows in that model was solved numerically for the case of flow rate of 250 mL/s with drug-laden spray(Q= 20, 40, 60 mL/s). Optimal parameters for mechanical drug aerosol targeting of predetermined areas was to be computed, for a given representative upper airways. From numerical flow visualization results, as flow-rate of drug-laden spray increases, the drag spray residue in oral cavity was increased and the distribution of drug spray in trachea and branches became more homogeneous.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.418-424
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• 2015

In this study, we proceed if there are any changes in binding ability of receptor-ligand in some degree of SA and in radioactive uptake from the corpus striatum based on small animal experiment in vivo based on the S.A values. By dividing 18F-Fallypride into 3 S.A values(high S.A : 43.29~74 GBq/umol, ordinary S.A : 20.72~29.23 GBq/umol, low S.A : 6.29~8.51 GBq/umol), we injected directly into the veins and performed 90 minutes of dynamic scan using Micro PET. After scanning, we compared and analyzed with Binding Potential (Binding Potential) from the bilateral striatum. high SA and low SA, ordinary SA and low SA showed significant differences. Also, in the image comparison using 18F-Fallypride show high radioactive uptake in the striatum at high SA and ordinary SA, but the radioactive uptake at low SA is lower than other two SA. Since 18F-Fallypride has affinity to dopamine D2/3 pharmacokinetic, the difference of Binding Potentials at decreased level of SA values was not that significant. However, further PET research of the corpus striatum using 18F-Fallypride is necessary because the differences in images and Binding Potentials at 6.5 times smaller SA values compared to high SA value showed were significant.

• Journal of radiological science and technology
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• v.38 no.3
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• pp.245-252
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• 2015

To obtain the best SNR (signal to noise ratio) due to changes in CTDI (computed tomography dose index) made for the purpose of setting the optimum image obtained by reducing the dose in abdominal CT. Abdominal CT scans of 59 patients a $400-499cm^2$ (n = 12), $500-599cm^2$ (n = 21), $600-699cm^2$ (n = 17), $700-799cm^2$ (n = 9) were separated by four groups and the effective dose was used in the Excel to get the area of the patient using the ImageJ program. Patients of CTDI, DLP, SNR, the effective dose were analyzed. Abdominal CT area was increased to 13 mGy in CTDI is 7.3 mGy, DLP to 732 in $394.4mGy{\cdot}cm$, also effective dose was 5.9 mSv increase in 11mSv. SNR is 15 dB was maintained at 12.7. CTDI according to the average of the abdominal area of 8.9 mGy, the average of the DLP was $481.54mGy{\cdot}cm$, the effective dose is calculated to be 7.2 mSV. Effective dose was calculated by multiplying the load factor of DLP in the abdomen showed no statistically significant difference of (p < .05), there was a significant difference in SNR (p > . 05). To improve image quality of abdominal CT scan image in consideration of the CTDI according to the volume of the patient it should be able to reduce the radiation exposure of the patients.

• The Korean Journal of Nuclear Medicine
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• v.29 no.4
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• pp.533-540
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• 1995

Attenuation correction is important in producing quantitative positron emission tomography (PET) images. Conventionally, photon attenuation effects are corrected using transmission measurements performed before tracer administration. The pre-injection transmission measurement approach may require a time delay between transmission and emission scans for the tracer studies requiring a long uptake period, about 45 minutes for F-18 deoxyglucose study. The time delay will limit patient throughput and increase the likelihood of patient motion. A technique lot performing simultaneous transmission and emission scans (T+E method) after the tracer injection has been validated. The T+E method substracts the emission counts contaminating the transmission measurements to produce accurate attenuation correction coefficients. This method has been evaluated in experiments using a cylindrical phantom filled with background water (5750 cc) containing $0.4{\mu}Ci/cc$ of F-18 fluoride ion and one insert cylinder (276 cc) containing $4.3{\mu}Ci/cc$. GE $Advance^{TM}$ PET scanner and Ge-68 rotating pin sources for transmission scanning were used for this investigation. Post-injection transmission scan and emission scan were peformed alternatively over time. The error in emission images corrected using post-infection transmission scan to emission images corrected transmission scan was 2.6% at the concentration of $1.0{\mu}Ci/cc$. No obvious differences in image quality and noise were apparent between the two images. The attenuation correction can be accomplished with post-injection transmission measurement using rotating pin sources and this method can significantly shorten the time between transmission and omission scans and thereby reduce the likelihood of patient motion and increase scanning throughput in PET.