• Progress in Medical Physics
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• v.17 no.4
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• pp.207-211
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• 2006

The advent of kV cone-beam computed tomography (CBCT) integrated with a linear accelerator allows for more accurate Image-guided radiotherapy (IGRT). IGRT is the technique that corrects target displacement based on internal body information. To do this, the CBCT Image set is acquired just before the beam is delivered and registered with the simulation CT Image set. In this study, we compare the registration results according to the CBCT's reconstruction quality (either high or medium). A total of 56 CBCT projection data from 6 patients were analyzed. The translation vector differences were within 1 mm in all but 3 cases. For rotation displacement difference, components of all three axes were considered and 3 out of 168 ($56{\times}3$ axes) cases showed more than lo of rotation differences.

• Journal of Radiation Protection and Research
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• v.35 no.2
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• pp.69-76
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• 2010

Prototype double-scattering Compton camera, which consists of three gamma-ray detectors, that is, two double-sided silicon strip detectors (DSSDs) as scatterer detectors and a NaI(Tl) scintillation detector as an absorber detector, could provide high imaging resolution with a compact system. In the present study, the energy resolution and the timing resolution of component detectors were measured, and the parameters affecting the energy resolution of the DSSD were examined in terms of equivalent noise charge (ENC). The energy resolutions of the DSSD-1 and DSSD-2 were, in average, $25.2keV{\pm}0.8keV$ FWHM and $31.8keV{\pm}4.6keV$ FWHM at the 59.5 keV peak of $^{241}Am$, respectively. The timing resolutions of the DSSD and NaI(Tl) scintillation detector were 57.25 ns FWHM and 7.98 ns FWHM, respectively. In addition, the Compton image was obtained for a point-like $^{137}Cs$ gamma source with double-scattering Compton camera. From the present experiment, the imaging resolution of 8.4 mm FWHM (angular resolution of $8.1^{\circ}$ FWHM), and the imaging sensitivity of $1.5{\times}10^{-7}$ (intrinsic efficiency of $1.9{\times}10^{-6}$) were obtained.

• The Korean Journal of Nuclear Medicine
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• v.29 no.4
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• pp.526-532
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• 1995

Introduction : $^{99m}Tc$-(V)-DMSA is a tumor seeking agent that has been used to image medullary carcinoma of thyroid, soft tissue sarcoma and lung cancer. This study was designed to assess the clinical role of $^{99m}Tc$-(V)-DMSA in the diagnosis of head and neck cancers. We has evaluated the diagnostic efficacy of planar and SPECT imaging using $^{99m}Tc$-(V)-DMSA. Patients and Method : Sixty-eight patients with head and neck mass were included in this study. All subjects were diagnosed by biopsy or surgery. Planar and SPECT images were obtained at 2 or 3 hour after intravenous injection of 740 MBq(20 mCi) $^{99m}Tc$-(V)-DMSA. Seventeen patients also underwent SPECT in aging using dual head camera. Result : The diagnostic sensitivity of $^{99m}Tc$-(V)-DMSA planar and SPECT imaging was 65% and 90%, and specificity was 80% and 66%, respectively. The sensitivity of planar imaging in squamous cell carcinoma was similar to overall sensitivity Six metastatic lesion were first diagnosed by scintigraphy. But benign lesions such as Kikuchi syndrome, tuberculous lymphadenitis also revealed increased uptake. Conclusion : $^{99m}Tc$-(V)-DMSA imaging seems to be a promising method in the evaluation of patients with head and neck mass. We recommend SPECT imaging to delineate anatomic localization of the lesion.

• Investigative Magnetic Resonance Imaging
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• v.18 no.1
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• pp.25-33
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• 2014

Purpose : To investigate whether quantitative parameters derived from Diffusion-weighted magnetic resonance imaging (DW-MRI) correlate with those of Dynamic contrast-enhanced MRI (DCE-MRI). Materials and Methods: Thirteen patients with pathologically or clinically proven bony metastasis who had undergone MRI prior to treatment were included. The voxel size was $1.367{\times}1.367{\times}5mm$. A dominant tumor was selected and the apparent diffusion coefficient (ADC) value and DCE-MRI parameters were obtained by matching voxels. DCE-MRI data were analyzed yielding estimates of $K^{trans}$ (volume transfer constant) and $v_e$. (extravascular extracellular volume fraction). Statistical analysis of ADC, $K^{trans}$, and $v_e$ value was conducted using Pearson correlation analyses. Results: Fifteen lesions in pelvic bones were evaluated. Of these, 11 showed a statistically significant correlation (P<0.05) between ADC and $K^{trans}$. The ADC and $K^{trans}$ were inversely related in 7 lesions and positively related in 4 lesions. This did not depend on the primary cancer or site of metastasis. The ADC and $v_e$ of 9 lesions correlated significantly. Of these, 4 lesions were inversely related and 5 lesions were positively related. Conclusion: Unlike our theoretic hypothesis, there was no consistent correlation between ADC values and $K^{trans}$ or between ADC values and $v_e$ in metastatic bone tumors.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.23-33
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• 2020

Recently, high-resolution images can be easily acquired using UAV (Unmanned Aerial Vehicle), so that it is possible to produce small area observation and spatial information at low cost. In particular, research on the generation of cover maps in crop production areas is being actively conducted for monitoring the agricultural environment. As a result of comparing classification performance by applying RF(Random Forest), SVM(Support Vector Machine) and CNN(Convolutional Neural Network), deep learning classification method has many advantages in image classification. In particular, land cover classification using satellite images has the advantage of accuracy and time of classification using satellite image data set and pre-trained parameters. However, UAV images have different characteristics such as satellite images and spatial resolution, which makes it difficult to apply them. In order to solve this problem, we conducted a study on the application of deep learning algorithms that can be used for analyzing agricultural lands where UAV data sets and small-scale composite cover exist in Korea. In this study, we applied DeepLab V3 +, FC-DenseNet (Fully Convolutional DenseNets) and FRRN-B (Full-Resolution Residual Networks), the semantic image classification of the state-of-art algorithm, to UAV data set. As a result, DeepLab V3 + and FC-DenseNet have an overall accuracy of 97% and a Kappa coefficient of 0.92, which is higher than the conventional classification. The applicability of the cover classification using UAV images of small areas is shown.

• Journal of Astronomy and Space Sciences
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• v.18 no.3
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• pp.231-238
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• 2001

A prototype CMOS (complementary metal oxide semiconductor) imaging system has been built and the possibility of applying to the application to astronomical observations has been investigated. The CCD (charge coupled device) image sensor has been the mainstay of image capture and astronomical imaging for the last 30 years, but CMOS devices have shown rapidly increasing success and have been adapted to many commercial imaging systems . Although the photometric performances and system noise of CMOS sensors are lower than that of CCD image sensors, CMOS Imaging system can be used to obtain general image capture for astronomical applications.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1041-1047
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• 2017

There are many methods for surveying the status of a road, and the use of unmanned aerial vehicle (UAV) photo is one such method. When the UAV images are too large to be processed and suspected to be redundant, a texture extraction technique is used to transform the data into a reduced set of feature representations. This is an important task in 3D simulation using UAV images because a huge amount of data can be inputted. This paper presents a texture extraction method from UAV images to obtain high-resolution images of bridges. The proposed method is in three steps: firstly, we use the 3D bridge model from the V-World database; secondly, textures are extracted from oriented UAV images; and finally, the extracted textures from each image are blended. The result of our study can be used to update V-World textures to a high-resolution image.

• Journal of the Korean Society of Radiology
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• v.12 no.4
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• pp.541-547
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• 2018

To evaluate the effect of dose and image quality for Chest Digital Tomosynthesis(CDT) using sensitivity and tube voltage(kV). CDT images of the phantom were acquired varying sensitivity 200, 320, 400 according to set tube voltage of 125 kV and 135 kV. The dose and Dose Area Product(DAP) according to change of sensitivity and kV were evaluated and Image quality was evaluated by PSNR, CNR, SNR using Image J. Dose were lowered 14~23% less than sensitivity 200, 125 kV and DAP were lowered 13~26% less than sensitivity 200, 125 kV. PSNR were over 27 dB, which were significant value and CNR, SNR were better as sensitivity value was lower. But there were different statistical significant to each item. CNR and SNR were not statistically significant at sensitivity 320, 135 kV(P>0.05). CDT can improve image quality with lower radiation dose using better than quality and correction power at digital radiography system.

• Progress in Medical Physics
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• v.17 no.2
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• pp.67-76
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• 2006

We evaluated the accuracy of a patient setup error correction due to reference image quality for a 2D-2D matching process. Digitally reconstructed radiographs (DRRs) generated by use of the Pinnacle3 and the Eclipse for various regions of a humanoid phantom and a patient for different CT slice thickness were employed as a reference images and kV X-ray Images from the On-Board Imager were registered to the reference DRRs. In comparison of the DRRs and profiles, DRR image quality was getting worse with an increase of CT image slice thickness. However there were only slight differences of setup errors evaluation between matching results for good and poor reference DRRs. Although DRR image quality did not strongly affect to the 2D-2D matching accuracy, there are still potential errors for matching procedure, therefore we recommend that DRR images are needed to be generated with less than 3mm slice thickness for 2D-2D matching.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.1
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• pp.167-174
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• 2010

In this paper, the ultraviolet rays images and aging judgement caused by surface contamination on 22.9[kV] class insulators was defined. UV images represented by the corona discharge are divided 3 types such as sunflower, jellyfish, amoeba and in detail, there are classified the progress mechanism of eight. In the field which is installed the power facilities, immediately, this judgement method can be found out the deteriorated parts of the power facilities. These steps are possible to judge the deterioration of power facilities through reliable data. Hereafter, this study as the diagnostic technology suitable for the sites is used.