• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.36 no.5
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• pp.402-407
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• 2010

Introduction: The planning of implant surgery is an important factor for the implant prosthesis. Stereolithographic (SLA) surgical stents based on a computer simulation are quite helpful for clinicians to perform the surgery as planned. Although many clinical and technical trials have been performed for computed tomography (CT)-guided implant stents to improve the surgical procedures and prosthetic treatment, there are still many problems to solve. We developed a system of a surgical guide based on 3 dimensional (3D) CT for implant therapy and achieved satisfactory results in the terms of planning and operation. Materials and Methods: Fifteen patients were selected and 30 implant fixtures were installed. The preoperative CT data for surgical planning were prepared after obtaining informed consent. Surgical planning was performed using the simulation program, Ondemend3D In2Guide. The stents were fabricated based on the simulation data containing information of the residual bone, the location of the nerve, and the expected design of the prostheses. After surgery with these customized stents, the accuracy and reproducibility of implant surgery were evaluated based on the computer simulation. The data of postoperative CT were used to confirm this system using the image fusion technique and compare the implant fixtures between the planned and implanted. Results: The mean error was 1.18 (${\pm}0.73$) mm at the occlusal center, 1.23 (${\pm}0.67$) mm at the apical center, and the axis error between the two fixtures was $3.25^{\circ}C$ (${\pm}3.00$). These stents showed superior accuracy in maxilla cases. The lateral side error at the apical center was significantly different from the error at the occlusal center but there were no significant differences between the premolars, 1st molars and 2nd molars. Conclusion: SLA surgical stents based on a computer simulation have the satisfactory accuracy and are expected to be useful for accurate planning and surgery if some errors can be improved.

• Progress in Medical Physics
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• v.24 no.4
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• pp.220-229
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• 2013

Respiratory-induced dynamic tumors render free-breathing cone-beam computed tomography (FBCBCT) images with motion artifacts complicating the task of quantifying the internal target volume (ITV). The purpose of this paper is to study the visibility of the revealed ITV when the imaging dose parameters, such as the kVp and mAs, are varied. The $Trilogy^{TM}$ linear accelerator with an On-Board Imaging ($OBI^{TM}$) system was used to acquire low-imaging-dose-mode (LIDM: 110 kVp, 20 mA, 20 ms/frame) and high-imaging-dose-mode (HIDM: 125 kVp, 80 mA, 25 ms/frame) FBCBCT images of a 3-cm diameter sphere (density=0.855 $g/cm^3$) moving in accordance to various sinusoidal breathing patterns, each with an unique inhalation-to-exhalation (I/E) ratio, amplitude, and period. In terms of image ITV contrast, there was a small overall average change of the ITV contrast when going from HIDM to LIDM of $6.5{\pm}5.1%$ for all breathing patterns. As for the ITV visible volume measurements, there was an insignificant difference between the ITV of both the LIDM- and HIDM-FBCBCT images with an average difference of $0.5{\pm}0.5%$, for all cases, despite the large difference in the imaging dose (approximately five-fold difference of ~0.8 and 4 cGy/scan). That indicates that the ITV visibility is not very sensitive to changes in imaging dose. However, both of the FBCBCT consistently underestimated the true ITV dimensions by up to 34.8% irrespective of the imaging dose mode due to significant motion artifacts, and thus, this imaging technique is not adequate to accurately visualize the ITV for image guidance. Due to the insignificant impact of imaging dose on ITV visibility, a plausible, alternative strategy would be to acquire more X-ray projections at the LIDM setting to allow 4DCBCT imaging to better define the ITV, and at the same time, maintain a reasonable imaging dose, i.e., comparable to a single HIDM-FBCBCT scan.

• Progress in Medical Physics
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• v.7 no.1
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• pp.37-52
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• 1996

Image-guided localized, water-suppressed in vivo $^1$H MR spectroscopic studies were performed on the patients with brain tumors, acute cerebral infarction and schizophrenia, and dogs. GE Signa 1.5 T whole-body MRI/MRS system using STEAM pulse sequence was used. Proton metabolite ratios relative to creatine (Cr) were obtained using a Marquart algorithm. In vivo $^1$H MR spectra in brain neoplastic tissues revealed the changes of signal intensities of N-acetylaspartate (NAA), choline (Cho) and lactate (Lac) resonances. The present results suggest that the observed metabolite alterations from localized, water-suppressed in vivo $^1$H MR spectroscopy can be useful as an index of brain tumors, cerebral infarction and schizophrenia, and provide good quality metabolic information of cerebral tissue in the field of thanato-chronology.

• Progress in Medical Physics
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• v.17 no.1
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• pp.24-31
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• 2006

Automated analysis software was developed to measure the magnitude of the intrafractional and interfractional errors during breast radiation treatments. Error analysis results are important for determining suitable planning target volumes (PTV) prior to Implementing breast-conserving 3-D conformal radiation treatment (CRT). The electrical portal imaging device (EPID) used for this study was a Portal Vision LC250 liquid-filled ionization detector (fast frame-averaging mode, 1.4 frames per second, 256X256 pixels). Twelve patients were imaged for a minimum of 7 treatment days. During each treatment day, an average of 8 to 9 images per field were acquired (dose rate of 400 MU/minute). We developed automated image analysis software to quantitatively analyze 2,931 images (encompassing 720 measurements). Standard deviations ($\sigma$) of intrafractional (breathing motion) and intefractional (setup uncertainty) errors were calculated. The PTV margin to include the clinical target volume (CTV) with 95% confidence level was calculated as $2\;(1.96\;{\sigma})$. To compensate for intra-fractional error (mainly due to breathing motion) the required PTV margin ranged from 2 mm to 4 mm. However, PTV margins compensating for intefractional error ranged from 7 mm to 31 mm. The total average error observed for 12 patients was 17 mm. The intefractional setup error ranged from 2 to 15 times larger than intrafractional errors associated with breathing motion. Prior to 3-D conformal radiation treatment or IMRT breast treatment, the magnitude of setup errors must be measured and properly incorporated into the PTV. To reduce large PTVs for breast IMRT or 3-D CRT, an image-guided system would be extremely valuable, if not required. EPID systems should incorporate automated analysis software as described in this report to process and take advantage of the large numbers of EPID images available for error analysis which will help Individual clinics arrive at an appropriate PTV for their practice. Such systems can also provide valuable patient monitoring information with minimal effort.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.1
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• pp.166-173
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• 2014

A noncontact nondestructive testing (NDT) method is proposed to detect the damage of pipeline structures and to identify the location of the damage. To achieve this goal, a scanning laser source actuation technique is utilized to generate a guided wave and scans a specific area to find damage location more precisely. The ND: YAG pulsed laser is used to generate Lamb wave and a piezoelectric sensor is installed to measure the structural responses. The measured responses are analyzed using three dimensional Fourier transformation (3DFT). The damage-sensitive features are extracted by wavenumber filtering based on the 3D FT. Then, flaw imaging techniques of a pipeline structures is conducted using the damage-sensitive features. Finally, the pipes with notches are investigated to verify the effectiveness and the robustness of the proposed NDT approach.

• Progress in Medical Physics
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• v.25 no.4
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• pp.264-270
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• 2014

This study developed a portable respiratory training device to improve breathing stability, which is an important element in using the CyberKnife Synchrony respiratory tracking device, one of the typical Stereotactic Radiation Therapy (SRT) devices. It produced an interface for users to be able to select one of two displays, a graph type and a bar type, supported an auditory system that helps them expect next respiration by improving a sense of rhythm of their respiratory period, and provided comfortable respiratory inducement. By targeting 5 applicants and applying individual respiratory period detected through a self-developed program, it acquired signal data of 'guide respiration' that induces breathing through signal data gained from 'free respiration' and an auditory system, and evaluated the usability by comparing deviation average values of respiratory period and respiratory amplitude. It could be identified that respiratory period decreased $55.74{\pm}0.14%$ compared to free respiration, and respiratory amplitude decreased $28.12{\pm}0.10%$ compared to free respiration, which confirmed the consistency and stability of respiratory. SBRT, developed based on these results, using the portable respiratory training device, for liver cancer or lung cancer, is evaluated to be able to help reduce delayed treatment time due to respiratory instability and improve treatment accuracy, and if it could be applied to developing respiratory training applications targeting an android-based portable device in the future, even use convenience and economic efficiency are expected.

• The Journal of Korean Society for Radiation Therapy
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• v.19 no.1
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• pp.43-49
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• 2007

Purpose: The aim of this study was the clinical implementation of IGRT using KV CBCT for setup correction in radiation therapy. Materials and Methods: We selected 9 patients (3 patient for each region; head, body, pelvis)and acquired 135 CBCT images with CLINAC iX (Varian medical system, USA). During the scan, the required time was measured. We analyzed the result in 3 direction; vertical, longitudinal, lateral. Results: The mean setup errors at the couch position of vertical, lateral, and longitudinal direction were 0.07, 0.12, and 0.1 cm in the head region, 0.3, 0.26, and 0.22 cm in the body region, 0.21, 0.18, and 0.15 cm in the pelvis region respectively. The mean time required for CBCT was $6{\sim}7$ minute. Conclusion: The CBCT on the LINAC provides the capacity for soft tissue imaging in the treatment position and real time monitoring during treatment delivery. With presented workflow, the setup correction within reasonable time for more accurate radiation therapy is possible. And it's image can be very useful for adaptive radiation therapy(ART) in the future with improved image quality.

• The Journal of Korean Society for Radiation Therapy
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• v.21 no.2
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• pp.67-74
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• 2009

Purpose: To evaluate the results of absorbed and effective doses using two different modes, standard mode (A-mode) and low-dose mode (B-mode) settings for prostate cancer IGRT from CBCT. Materials and Methods: This experimental study was obtained using Clinac iX integrated with On Board Imager (OBI) System and CBCT. CT images were obtained using a GE Light Speed scanner. Absorbed dose to organs from ICRP recommendations and effective doses to body was performed using A-mode and B-mode CBCT. Measurements were performed using a Anderson rando phantom with TLD-100 (Thermoluminescent dosimeters). TLD-100 were widely used to estimate absorbed dose and effective dose from CBCT with TLD System 4000 HAWSHAW. TLD-100 were calibrated to know sensitivity values using photon beam. The measurements were repeated three times for prostate center. Then, Evaluations of effective dose and absorbed dose were performed among the A-mode and B-mode CBCT. Results: The prostate absorbed dose from A-mode and B mode CBCT were 5.5 cGy 1.1 cGy per scan. Respectively Effective doses to body from A mode and B-mode CBCT were 19.1 mSv, 4.4 mSv per scan. Effective dose from A-mode CBCT were approximately 4 times lower than B-mode CBCT. Conclusion: We have shown that it is possible to reduce the effective dose considerably by low dose mode(B-mode) or lower mAs CBCT settings for prostate cancer IGRT. Therefore, we should try to select B-mode or low condition setting to decrease extra patient dose during the IGRT for prostate cancer as possible.

• The Journal of Korean Society for Radiation Therapy
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• v.35
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• pp.41-51
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• 2023

Purpose: This study compares and analyzes the image quality of 3D-CBCT(Cone Beam Computed-Tomography) and Gated CBCT according to baseline changes during SBRT(Stereotactic Body RadioTherapy) in lung cancer patients to find a useful CBCT method for correcting movement due to breathing Materials and methods : Insert a solid tumor material with a diameter of 3 cm into the QUASAR^TM phantom. 4-Dimentional Computed-Tomography(4DCT) images were taken with a speed of the phantom at period 3 sec and a maximum amplitude of 20 mm. Using the contouring menu of the computerized treatment planning system Eclipse^TM Gross Tumor Volume was outlined on solid tumor material. Set-up the same as when acquiring a 4DCT image using Truebeam STx^TM, breathing patterns with baseline changes of 1 mm, 3 mm, and 5 mm were input into the phantom to obtain 3D-CBCT (Spotlight, Full) and Gated-CBCT (Spotlight, Full) images five times repeatedly. The acquired images were compared with the Signal-to-Noise Ratio(SNR), Contrast-to-Noise Ratio(CNR), Tumor Volume Length, and Motion Blurring Ratio(MBR) based on the 4DCT image. Results: The average Signal-to-Noise Ratio, Contrast-to-Noise Ratio, Tumor Volume Length and Motion Blurring Ratio of Spotlight Gated CBCT images were 13.30±0.10%, 7.78±0.16%, 3.55±0.17%, 1.18±0.06%. As a result, Spotlight Gated-CBCT images according to baseline change showed better values than Spotligtht 3D-CBCT images. Also, the average Signal-to-Noise Ratio, Contrast-to-Noise Ratio, Tumor Volume Length and Motion Blurring Ratio of Full Gated CBCT images were 12.80±0.11%, 7.60±0.11%, 3.54±0.16%, 1.18±0.05%. As a result Full GatedCBCT images according to baseline change showed better values than Full 3D-CBCT images. Conclusion : Compared to 3D-CBCT images, Gated-CBCT images had better image quality according to the baseline change, and the effect of Motion Blurring Artifacts caused by breathing was small. Therefore, it is considered useful to image guided using Gated-CBCT when a baseline change occurs due to difficulty in regular breathing during SBRT that exposes high doses in a short period of time

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.312-320
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• 2012

In this study, we introduce a new design methodology of a granular-oriented self-organizing polynomial neural networks (GoSOPNNs) that is based on multi-layer perceptron with Context-based Polynomial Neurons (CPNs) or Polynomial Neurons (PNs). In contrast to the typical architectures encountered in polynomial neural networks (PNN), our main objective is to develop a methodological design strategy of GoSOPNNs as follows : (a) The 1st layer of the proposed network consists of Context-based Polynomial Neuron (CPN). In here, CPN is fully reflective of the structure encountered in numeric data which are granulated with the aid of Context-based Fuzzy C-Means (C-FCM) clustering method. The context-based clustering supporting the design of information granules is completed in the space of the input data while the build of the clusters is guided by a collection of some predefined fuzzy sets (so-called contexts) defined in the output space. (b) The proposed design procedure being applied at each layer of GoSOPNN leads to the selection of preferred nodes of the network (CPNs or PNs) whose local characteristics (such as the number of contexts, the number of clusters, a collection of the specific subset of input variables, and the order of the polynomial) can be easily adjusted. These options contribute to the flexibility as well as simplicity and compactness of the resulting architecture of the network. For the evaluation of performance of the proposed GoSOPNN network, we describe a detailed characteristic of the proposed model using a well-known learning machine data(Automobile Miles Per Gallon Data, Boston Housing Data, Medical Image System Data).