• Journal of the Korean Association of Oral and Maxillofacial Surgeons
• /
• v.25 no.4
• /
• pp.295-303
• /
• 1999

Presented in this paper are the experimental results that measure rapid prototyping (RP) errors in 3D medical models. We identified various factors that can cause dimensional errors when producing RP models, specifically in maxillofacial areas. For the experiment, we used a human dry skull. A number of linear measurements based on landmarks were first obtained on the skull. This was followed by CT scanning, 3D model reconstruction, and RP model fabrication. The landmarks were measured again on both the reconstructed models and the physical RP models, and these were compared with those on dry skull. We focused on major sources of errors, such as CT scanning, conversion from CT data to STL models, and RP model fabrication. The results show that the overall error from skull to RP is $0.64{\times}0.36mm(0.71{\times}0.66%)$ in absolute value. This indicates that the RP technology can be acceptable in the real clinical applications. A clinical case that has applied RP models successfully for treatment planning and surgical rehearsal is presented. Although the use of RP models is rare in the medical area yet, we believe RP is promising in that it has a great potential in developing new tools which can aid diagnosis, treatment planning, surgical rehearsal, education, and so on.

• Analytical Science and Technology
• /
• v.10 no.4
• /
• pp.300-306
• /
• 1997

The effective resolution of the direct current potential drop (DCPD) method for crack length determination is strongly affected by a number of factors including wire locations and calibration method. In the present study, the effects of wire locations, thermal EMF and reference probe locations on the accuracy of calibration methods, including Hicks-Pickard equation and Johnson's equation, were examined with the CT specimens which were nine times larger than the standard specimen. In light of experimental results, it was found that Hicks-Pickard equation can accurately represent the a/W-V/Vo relationship when current input wire is located at the load line. It was also found that the accuracy of DCPD method can be greatly improved with the thermal EMF calibration and the use of Vo value at a/W = 0.241. The use of reference potential was found to be impractical when current input wire is located at the load line.

• Journal of International Society for Simulation Surgery
• /
• v.1 no.1
• /
• pp.37-40
• /
• 2014

Purpose For living donor liver transplantation, liver segmentation is difficult due to the variability of its shape across patients and similarity of the density of neighbor organs such as heart, stomach, kidney, and spleen. In this paper, we propose an automatic segmentation of the liver using multi-planar anatomy and deformable surface model in portal phase of abdominal contrast-enhanced CT images. Method Our method is composed of four main steps. First, the optimal liver volume is extracted by positional information of pelvis and rib and by separating lungs and heart from CT images. Second, anisotropic diffusing filtering and adaptive thresholding are used to segment the initial liver volume. Third, morphological opening and connected component labeling are applied to multiple planes for removing neighbor organs. Finally, deformable surface model and probability summation map are performed to refine a posterior liver surface and missing left robe in previous step. Results All experimental datasets were acquired on ten living donors using a SIEMENS CT system. Each image had a matrix size of $512{\times}512$ pixels with in-plane resolutions ranging from 0.54 to 0.70 mm. The slice spacing was 2.0 mm and the number of images per scan ranged from 136 to 229. For accuracy evaluation, the average symmetric surface distance (ASD) and the volume overlap error (VE) between automatic segmentation and manual segmentation by two radiologists are calculated. The ASD was $0.26{\pm}0.12mm$ for manual1 versus automatic and $0.24{\pm}0.09mm$ for manual2 versus automatic while that of inter-radiologists was $0.23{\pm}0.05mm$. The VE was $0.86{\pm}0.45%$ for manual1 versus automatic and $0.73{\pm}0.33%$ for manaual2 versus automatic while that of inter-radiologist was $0.76{\pm}0.21%$. Conclusion Our method can be used for the liver volumetry for the pre-surgery planning of living donor liver transplantation.

• Journal of radiological science and technology
• /
• v.43 no.6
• /
• pp.503-509
• /
• 2020

This study aims to develop a patient-specific radiation exposure dose prediction model based on anthropometric data that can be easily measurable during CT examination, and to be used as basic data for DRL setting and radiation dose management system in the future. In addition, among the machine learning algorithms, the most suitable model for predicting exposure doses is presented. The data used in this study were chest CT scan data, and a data set was constructed based on the data including the patient's anthropometric data. In the pre-processing and sample selection of the data, out of the total number of samples of 250 samples, only chest CT scans were performed without using a contrast agent, and 110 samples including height and weight variables were extracted. Of the 110 samples extracted, 66% was used as a training set, and the remaining 44% were used as a test set for verification. The exposure dose was predicted through random forest, linear regression analysis, and SVM algorithm using Orange version 3.26.0, an open software as a machine learning algorithm. Results Algorithm model prediction accuracy was R^2 0.840 for random forest, R^2 0.969 for linear regression analysis, and R^2 0.189 for SVM. As a result of verifying the prediction rate of the algorithm model, the random forest is the highest with R^2 0.986 of the random forest, R^2 0.973 of the linear regression analysis, and R^2 of 0.204 of the SVM, indicating that the model has the best predictive power.

• Journal of the Korean Society of Radiology
• /
• v.16 no.1
• /
• pp.25-34
• /
• 2022

Brain computed tomography (CT) is useful for brain lesion diagnosis, such as brain hemorrhage, due to non-invasive methodology, 3-dimensional image provision, low radiation dose. However, there has been numerous misdiagnosis owing to a lack of radiologist and heavy workload. Recently, object detection technologies based on artificial intelligence have been developed in order to overcome the limitations of traditional diagnosis. In this study, the applicability of a deep learning-based YOLOv5s model was evaluated for brain hemorrhage detection using brain CT images. Also, the effect of hyperparameters in the trained YOLOv5s model was analyzed. The YOLOv5s model consisted of backbone, neck and output modules. The trained model was able to detect a region of brain hemorrhage and provide the information of the region. The YOLOv5s model was trained with various activation functions, optimizer functions, loss functions and epochs, and the performance of the trained model was evaluated in terms of brain hemorrhage detection accuracy and training time. The results showed that the trained YOLOv5s model is able to provide a bounding box for a region of brain hemorrhage and the accuracy of the corresponding box. The performance of the YOLOv5s model was improved by using the mish activation function, the stochastic gradient descent (SGD) optimizer function and the completed intersection over union (CIoU) loss function. Also, the accuracy and training time of the YOLOv5s model increased with the number of epochs. Therefore, the YOLOv5s model is suitable for brain hemorrhage detection using brain CT images, and the performance of the model can be maximized by using appropriate hyperparameters.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.25 no.2
• /
• pp.15-24
• /
• 2021

Purpose SPECT/CT was noted for its excellent correction method and qualitative functions based on fusion images in the early stages of dissemination, and interest in and utilization of quantitative functions has been increasing with the recent introduction of companion diagnostic therapy(Theranostics). Unlike PET/CT, various conditions like the type of collimator and detector rotation are a challenging factor for image acquisition and reconstruction methods at absolute quantification of SPECT/CT. Therefore, in this study, We want to find out the effect on the radioactivity concentration estimate by the increase or decrease of the total acquisition time according to the number of projections and the acquisition time per projection among SPECT/CT imaging conditions. Materials and Methods After filling the 9,293 ml cylindrical phantom with sterile water and diluting 99mTc 91.76 MBq, the standard image was taken with a total acquisition time of 600 sec (10 sec/frame × 120 frames, matrix size 128 × 128) and also volume sensitivity and the calibration factor was verified. Based on the standard image, the comparative images were obtained by increasing or decreasing the total acquisition time. namely 60 (-90%), 150 (-75%), 300 (-50%), 450 (-25%), 900 (+50%), and 1200 (+100%) sec. For each image detail, the acquisition time(sec/frame) per projection was set to 1.0, 2.5, 5.0, 7.5, 15.0 and 20.0 sec (fixed number of projections: 120 frame) and the number of projection images was set to 12, 30, 60, 90, 180 and 240 frames(fixed time per projection:10 sec). Based on the coefficients measured through the volume of interest in each acquired image, the percentage of variation about the contrast to noise ratio (CNR) was determined as a qualitative assessment, and the quantitative assessment was conducted through the percentage of variation of the radioactivity concentration estimate. At this time, the relationship between the radioactivity concentration estimate (cps/ml) and the actual radioactivity concentration (Bq/ml) was compared and analyzed using the recovery coefficient (RC_Recovery Coefficients) as an indicator. Results The results [CNR, radioactivity Concentration, RC] by the change in the number of projections for each increase or decrease rate (-90%, -75%, -50%, -25%, +50%, +100%) of total acquisition time are as follows. [-89.5%, +3.90%, 1.04] at -90%, [-77.9%, +2.71%, 1.03] at -75%, [-55.6%, +1.85%, 1.02] at -50%, [-33.6%, +1.37%, 1.01] at -25%, [-33.7%, +0.71%, 1.01] at +50%, [+93.2%, +0.32%, 1.00] at +100%. and also The results [CNR, radioactivity Concentration, RC] by the acquisition time change for each increase or decrease rate (-90%, -75%, -50%, -25%, +50%, +100%) of total acquisition time are as follows. [-89.3%, -3.55%, 0.96] at - 90%, [-73.4%, -0.17%, 1.00] at -75%, [-49.6%, -0.34%, 1.00] at -50%, [-24.9%, 0.03%, 1.00] at -25%, [+49.3%, -0.04%, 1.00] at +50%, [+99.0%, +0.11%, 1.00] at +100%. Conclusion In SPECT/CT, the total coefficient obtained according to the increase or decrease of the total acquisition time and the resulting image quality (CNR) showed a pattern that changed proportionally. On the other hand, quantitative evaluations through absolute quantification showed a change of less than 5% (-3.55 to +3.90%) under all experimental conditions, maintaining quantitative accuracy (RC 0.96 to 1.04). Considering the reduction of the total acquisition time rather than the increasing of the image acquiring time, The reduction in total acquisition time is applicable to quantitative analysis without significant loss and is judged to be clinically effective. This study shows that when increasing or decreasing of total acquisition time, changes in acquisition time per projection have fewer fluctuations that occur in qualitative and quantitative condition changes than the change in the number of projections under the same scanning time conditions.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.16 no.2
• /
• pp.81-86
• /
• 2012

Purpose : Combined MR/PET scanners that use the MRI for PET AC face the challenge of absent surface coils in MR images and thus cannot directly account for attenuation in the coils. To make up for the weak point of MR attenuation correction, Three Modality System (PET/CT +MR) were used in Severance hospital. The goal of this work was to investigate the effects of MR Torso Coil on CT attenuation correction for PET. Materials and Methods : PET artifacts were evaluated when the MR Torso Coil was present of CTAC data with changing various kV and mA in uniformity water phantom and 1994 NEMA cylinderical phantom. They evaluated and compared the following two scenarios: (1) The uniform cylinder phantom and the MR Torso Coil scanned and reconstructed using CT-AC; (2) 1994 NEMA cylinderical phantom and the MR Torso Coil scanned and reconstructed using CT-AC. Results : Streak artifacts were present in CT images containing the MR Torso Coil due to metal components. These artifacts persisted after the CT images were converted for PET-AC. CT scans tended to over-estimate the linear attenuation coefficient when the kV and mA is increasing of the metal components when using conventional methods for converting from CT number. Conclusion : The presence of MR coils during PET/CT scanning can cause subtle artifacts and potentially important quantification errors. Alternative CT techniques that mitigate artifacts should be used to improve AC accuracy. When possible, removing segments of an MR coil prior to the PET/CT exam is recommended. Further, MR coils could be redesigned to reduce artifacts by rearranging placement of the most attenuating materials.

• Journal of the Korean Academy of Esthetic Dentistry
• /
• v.28 no.1
• /
• pp.4-17
• /
• 2019

Nowadays, Cone-Beam CT is widely supplied in dental clinics, the distribution rate in south korea is highly ranked worldwidely. Recently, The number of Cone-Beam CTs reached 10 thousands according to national healthcare system report. Also, dental manufacturers released many kinds of In-house 3D digital printers, the distribution rate of which rises rapidly in dental clinics. Accordingly, using Cone-Beam CT data and Intraloral scan data, the application of implant guide surgery is widespread in a unit of private clinic. Through the previous articles, the latest methods of computer-guided implant surgery are reviewed, and also the considerations for precise and reliable guide surgery are summarized.

• Progress in Medical Physics
• /
• v.25 no.2
• /
• pp.100-109
• /
• 2014

In stereotactic body radiotherapy (SBRT), the accurate location of treatment sites should be guaranteed from the respiratory motions of patients. Lots of studies on this topic have been conducted. In this letter, a new verification method simulating the real respiratory motion of heterogenous treatment regions was proposed to investigate the accuracy of lung SBRT for Volumetric Modulated Arc Therapy. Based on the CT images of lung cancer patients, lung phantoms were fabricated to equip in $QUASAR^{TM}$ respiratory moving phantom using 3D printer. The phantom was bisected in order to measure 2D dose distributions by the insertion of EBT3 film. To ensure the dose calculation accuracy in heterogeneous condition, The homogeneous plastic phantom were also utilized. Two dose algorithms; Analytical Anisotropic Algorithm (AAA) and AcurosXB (AXB) were applied in plan dose calculation processes. In order to evaluate the accuracy of treatments under respiratory motion, we analyzed the gamma index between the plan dose and film dose measured under various moving conditions; static and moving target with or without gating. The CT number of GTV region was 78 HU for real patient and 92 HU for the homemade lung phantom. The gamma pass rates with 3%/3 mm criteria between the plan dose calculated by AAA algorithm and the film doses measured in heterogeneous lung phantom under gated and no gated beam delivery with respiratory motion were 88% and 78%. In static case, 95% of gamma pass rate was presented. In the all cases of homogeneous phantom, the gamma pass rates were more than 99%. Applied AcurosXB algorithm, for heterogeneous phantom, more than 98% and for homogeneous phantom, more than 99% of gamma pass rates were achieved. Since the respiratory amplitude was relatively small and the breath pattern had the longer exhale phase than inhale, the gamma pass rates in 3%/3 mm criteria didn't make any significant difference for various motion conditions. In this study, the new phantom model of 4D dose distribution verification using patient-specific lung phantoms moving in real breathing patterns was successfully implemented. It was also evaluated that the model provides the capability to verify dose distributions delivered in the more realistic condition and also the accuracy of dose calculation.

• Journal of Biomedical Engineering Research
• /
• v.43 no.6
• /
• pp.434-440
• /
• 2022

Liver transplantation is a critical used treatment method for patients with end-stage liver disease. The number of cases of living donor liver transplantation is increasing due to the imbalance in needs and supplies for brain-dead organ donation. As a result, the importance of the accuracy of the donor's suitability evaluation is also increasing rapidly. To measure the donor's liver volume accurately is the most important, that is absolutely necessary for the recipient's postoperative progress and the donor's safety. Therefore, we propose liver segmentation in abdominal CT images from pre-operation, POD 7, and POD 63 with a two-dimensional U-Net. In addition, we introduce an algorithm to measure the volume of the segmented liver and measure the hepatectomy rate and regeneration rate of pre-operation, POD 7, and POD 63. The performance for the learning model shows the best results in the images from pre-operation. Each dataset from pre-operation, POD 7, and POD 63 has the DSC of 94.55 ± 9.24%, 88.40 ± 18.01%, and 90.64 ± 14.35%. The mean of the measured liver volumes by trained model are 1423.44 ± 270.17 ml in pre-operation, 842.99 ± 190.95 ml in POD 7, and 1048.32 ± 201.02 ml in POD 63. The donor's hepatectomy rate is an average of 39.68 ± 13.06%, and the regeneration rate in POD 63 is an average of 14.78 ± 14.07%.