Journal of International Society for Simulation Surgery
/
v.3
no.1
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pp.16-21
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2016
Computed tomography (CT) can completely digitize the interior and the exterior of nearly any object without any destruction. Generally, the resolution for industrial CT is below a few microns. The industrial CT scanning, however, has a limitation because it requires long measuring and processing time. Whereas, 2D X-ray imaging is fast. In this paper, we propose a novel concept of 3D non-destructive inspection technique using the advantages of both micro-CT and dual X-ray images. After registering the master object’s CT data and the sample objects’ dual X-ray images, 3D non-destructive inspection is possible by analyzing the matching results. Calculation for the registration is accelerated by parallel computing using graphics processing unit (GPU).
Objective: To evaluate the technical applicability of a semiautomatic three-dimensional (3D) hybrid CT segmentation method for the quantification of right ventricular mass in patients with cardiovascular disease. Materials and Methods: Cardiac CT (270 cardiac phases) was used to quantify right ventricular mass using a semiautomatic 3D hybrid segmentation method in 195 patients with cardiovascular disease. Data from 270 cardiac phases were divided into subgroups based on the extent of the segmentation error (no error; ≤ 10% error; > 10% error [technical failure]), defined as discontinuous areas in the right ventricular myocardium. The reproducibility of the right ventricular mass quantification was assessed. In patients with no error or < 10% error, the right ventricular mass was compared and correlated between paired end-systolic and end-diastolic data. The error rate and right ventricular mass were compared based on right ventricular hypertrophy groups. Results: The quantification of right ventricular mass was technically applicable in 96.3% (260/270) of CT data, with no error in 54.4% (147/270) and ≤ 10% error in 41.9% (113/270) of cases. Technical failure was observed in 3.7% (10/270) of cases. The reproducibility of the quantification was high (intraclass correlation coefficient = 0.999, p < 0.001). The indexed mass was significantly greater at end-systole than at end-diastole (45.9 ± 22.1 g/m2 vs. 39.7 ± 20.2 g/m2, p < 0.001), and paired values were highly correlated (r = 0.96, p < 0.001). Fewer errors were observed in severe right ventricular hypertrophy and at the end-systolic phase. The indexed right ventricular mass was significantly higher in severe right ventricular hypertrophy (p < 0.02), except in the comparison of the end-diastolic data between no hypertrophy and mild hypertrophy groups (p > 0.1). Conclusion: CT quantification of right ventricular mass using a semiautomatic 3D hybrid segmentation is technically applicable with high reproducibility in most patients with cardiovascular disease.
Background: In recent events of the coronavirus disease 2019 (COVID-19) pandemic, computed tomography (CT) scans are being globally used as a complement to the reverse-transcription polymerase chain reaction (RT-PCR) tests. It will be important to be aware of major organ dose levels, which are more relevant quantity to derive potential long-term adverse effect, for Korean pediatric and adult patients undergoing CT for COVID-19. Materials and Methods: We calculated organ dose conversion coefficients for Korean pediatric and adult CT patients directly from Korean pediatric and adult computational phantoms combined with Monte Carlo radiation transport techniques. We then estimated major organ doses delivered to the Korean child and adult patients undergoing CT for COVID-19 combining the dose conversion coefficients and the international survey data. We also compared our Korean dose conversion coefficients with those from Caucasian reference pediatric and adult phantoms. Results and Discussion: Based on the dose conversion coefficients we established in this study and the international survey data of COVID-19-related CT scans, we found that Korean 7-year-old child and adult males may receive about 4-32 mGy and 3-21 mGy of lung dose, respectively. We learned that the lung dose conversion coefficient for the Korean child phantom was up to 1.5-fold greater than that for the Korean adult phantom. We also found no substantial difference in dose conversion coefficients between Korean and Caucasian phantoms. Conclusion: We estimated radiation dose delivered to the Korean child and adult phantoms undergoing COVID-19-related CT examinations. The dose conversion coefficients derived for different CT scan types can be also used universally for other dosimetry studies concerning Korean CT scans. We also confirmed that the Caucasian-based CT organ dose calculation tools may be used for the Korean population with reasonable accuracy.
Journal of Institute of Control, Robotics and Systems
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v.22
no.8
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pp.597-602
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2016
In image guided surgery, a patient registration process is a critical process for the successful operation, which is required to use pre-operative images such as CT and MRI during operation. Though several patient registration methods have been studied, we concentrate on one method that utilizes 3D surface measurement data in this paper. First, a hand-held 3D surface measurement device measures the surface of the patient, and secondly this data is matched with CT or MRI data using optimization algorithms. However, generally used ICP algorithm is very slow without a proper initial location and also suffers from local minimum problem. Usually, this problem is solved by manually providing the proper initial location before performing ICP. But, it has a disadvantage that an experience user has to perform the method and also takes a long time. In this paper, we propose a method that can accurately find the proper initial location automatically. The proposed method finds the proper initial location for ICP by converting 3D data to 2D curvature images and performing image matching. Curvature features are robust to the rotation, translation, and even some deformation. Also, the proposed method is faster than traditional methods because it performs 2D image matching instead of 3D point cloud matching.
Subhanik Purkayastha;Yanhe Xiao;Zhicheng Jiao;Rujapa Thepumnoeysuk;Kasey Halsey;Jing Wu;Thi My Linh Tran;Ben Hsieh;Ji Whae Choi;Dongcui Wang;Martin Vallieres;Robin Wang;Scott Collins;Xue Feng;Michael Feldman;Paul J. Zhang;Michael Atalay;Ronnie Sebro;Li Yang;Yong Fan;Wei-hua Liao;Harrison X. Bai
Korean Journal of Radiology
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v.22
no.7
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pp.1213-1224
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2021
Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion: CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.
Purpose Recently PET/CT image's attenuation correction is used CTAC(Computed Tomgraphy Attenuation Correction). it can quantitative evaluation by SUV(Standard Uptake Value). This study's purpose is to evaluate SUV and to find proper CT kernel using CTAC with applied various CT kernel to PET/CT construction. Materials and Methods Biograph mCT 64 was used for the equipment. We were performed on 20 patients who had examed at our hospital from february through March 2017. Using NEMA IEC Body Phantom, The data was reconstructed PET/CT images with CTAC appiled various CT kernel. ANOVA was used to evaluated the significant difference in the result. Results The result of measuring the radioactivity concentration of Phantom was B45F 96% and B80F 6.58% against B08F CT kernel, each respectively. the SUVmax increased to B45F 0.86% and B80F 6.54% against B08F CT kernel, In case of patient's parts data, the Lung SUVmax increased to B45F 1.6% and B80F 6.6%, Liver SUVmax increased to B45F 0.7% and B80F 4.7%, and Bone SUVmax increased to B45F 1.3% and B80F 6.2%, respectively. As for parts of patient's about Standard Deviation(SD), the Lung SD increased to B45F 4.2% and B80F 15.4%, Liver SD increased to B45F 2.1% and B80F 11%, and Bone SD increased to B45F 2.3% and B80F 14.7%, respectively. There was no significant difference discovered in three CT kernel (P >.05). Conclusion When using increased noise CT kernel for PET/CT reconstruction, It tends to change both SUVmax and SD in ROI(region of interest), Due to the increase the CT kernel number, Sharp noise increased in ROI. so SUVmax and SD were highly measured, but there was no statistically significant difference. Therefore Using CT kernel of low variation of SD occur less variation of SUV.
Park, Sung-Min;Kim, Keung-Sik;Kang, Seong-Min;Yoo, Beong-Gyu;Lee, Ki-Bae
Korean Journal of Digital Imaging in Medicine
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v.17
no.1
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pp.13-18
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2015
Purpose : Skip the repetitive HRCT axial scan in order to reduce the exposure of patients during chest HRCT scan, Helical Scan Data into a reconstructed image, and exposure of the patient change and visually evaluate the usefulness of the HRCT images. Materials and method : Patients were enrolled in the survey are 50 people who underwent chest CT scans of patients who presented to the hospital from January 2015 to March 2015. 50 people surveyed 22 people men and 28 people women people showed an average distribution of 30 to 80 years age was 48 years. 50 patients to Somatom Sensation 64 ch (Siemens) model with 120 kVp tube voltage to a reference mAs tube current to mAs (Care dose, Siemens) as a whole, including the lungs and the chest CT scan was performed. Scan upon each patient CARE dose 4D (Automatic exposure control, Siemens Medical Solution Erlangen, Germany) was to maintain the proper radiation dose scan every cross-section through a device that automatically adjusts the tube current of. CT scan is the rotation time of the Tube slice collimation, slice width 0.6 mm, pitch factor was made under the terms of 1.4. CT scan obtained after the raw data (raw data) to the upper surface of the axial images and coronal images for each slice thickness 1 mm, 5 mm intervals in the high spatial frequency calculation method (hight spatial resolution algorithm, B60 sharp) was the use of the lung window center -500 HU, windows were reconstructed into images in the interval -1000 HU to see. Result : 1. Measure the total value of DLP 50 patients who proceed to chest CT group A (Helical Scan after scan performed with HRCT) and group B (Helical Scan after the HR image reconstruction to the original data) compared with the group divided, analysis As a result of the age, but show little difference for each age group it had a decreased average dose of about 9%. 2. A Radiation read the results of the two Radiologist and a doctor upper lobe and middle lobe of the lung takes effect the visual evaluation is not a big difference between the two images both, depending on the age of the patient, especially if the blood vessels of the lower lobe (A: 3.4, B: 4.6) and bronchi(A: 3.8, B4.7) image shake caused by breathing in anxiety (blurring lead) to the original data (raw data) showed that the reconstructed image is been more useful in diagnostic terms. Conclusion : Scan was confirmed a continuous, rapid motion video to get Helical scan is much lower lobe lung reduction in visual blurring, Helical scan data to not repeat the examination by obtaining HRCT images reorganization reduced the exposure of the patient.
Purpose: As the number of domestic medical institutions installing PET/CT is increasing rapidly, the transfer of PET/CT images among medical institutions is also increasing. Thus, it is necessary to collect the comparative SUV data from several medical institutions' PET/CT systems through a phantom study which semi-quantitatively compares the SUV on one bed, the change scale of the SUV on the slices, and the time of measuring. The phantom study to find differences among the SUVs from various PET/CT offers the opportunity to obtain the reliability of the SUV in PET/CT images. Materials and Methods: Ten PET/CT systems from medical institutions in Korea were used. To obtain the accurate data, the study has been using the radiation detector of Korea Research Institute of Standards and Science to verify. The internal structures of NEMA $phantom^{TM}$ were removed and Six thousand milliliters of distilled water which has 1mCi of $^{18}F$-FDG put into the phantom. The water was properly integrated with $^{18}F$-FDG using magnetic stirrer. The images were acquired at 60, 70, 80, 90, 100, 110 and 120-minutes for 3 minute each. Two hundred square centimeters of region of interests were placed and analyzed. To confirm the usefulness, the correction-table came out from patients' data. Results: The coefficient of variability of the SUV from -11.0 to 9.90 % fell into the range of international standards(${\pm}10%$) along with the SUV on a bed, the change scale of the SUV on the slices, and the time of measuring, except one PET/CT system. Using the data of the differences among the SUVs, we came to withdraw the correction-table ranging from 0.803 to 1.246. The correction-table was confirmed its usefulness through Linear Regression Analysis which was applied to normal cases. Conclusions: Although studies have been made on the variation of the SUV, there is little attention on the standardization of the SUV. Based on this study of the quantitatively comparable data about the SUV accommodating the correction-table, it would help to have more corrective diagnosis.
Bone density is one of the factors in the early failure of dental implants and doctors should make a preoperative assessment of jaw bone density using patient's CT data before dental implant surgery in order to find out whether the patient has osteoporosis and osteopenia. The main goal of this study was to propose a method that based on image processing techniques in order to provide accurate information about where to drill and place an abutment screw of implants in the jaw bone for doctors and reduce human activity for the estimation of the local cancellous bone density of mandible using CT data. The experiment was performed on a computed tomography data of the jaw bone of two different individuals. We assumed that the result of the estimation of jaw bone density depends on the angle of drilling and average HU (Hounsfield Unit) values were used to evaluate the quality of local cancellous bone density of mandible. As a result of this study, we have been developed a toolbox that can be used to estimate jaw bone density automatically and found a positive correlation between the angle of the drill and time complexity but a negative correlation between the diameter of the drill and time complexity.
Park, So Young;Jung, Jae Yun;Kwak, Young Ho;Kim, Do Kyun;Suh, Dong Bum
Journal of Trauma and Injury
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v.25
no.4
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pp.152-158
/
2012
Purpose: To understand the epidemiology of head trauma and the utilization of brain CT in Korea, we analyzed a national sampling data set, the National Patient Sample obtained from the Health Insurance Review and Assessment Service. Methods: We retrospectively collected and analyzed demographic and clinical data on enrolled patients from the National Patient Sample based on medical claims data for 2009. The data included patient's age, sex, treatment date, diagnosis codes, procedure codes related with CT, holiday or night consultation fee, and fee for emergency management services. Results: In 2009, the estimated population with head trauma was 819,059(1.8%), and the rate of brain CT utilization was 22.4%. Children ages 5 to 15 were the most commonly injured group(22.8%), but had the lowest brain CT utilization(16.5%). The mean age of the estimated population with head trauma was $34.9{\pm}0.5years$ old, and male patients accounted for 60.5% of that population. Intracranial injury was found in 8.6% of all head traumas, and the rate of intracranial injury in children was lower than it was in adults(4.1% vs. 10.9%, p<0.001). Twenty- three percent of patients with head trauma visited the emergency department (ED). More patients with head trauma visited medical facilities in the daytime on weekdays(66.5% vs. 33.5%, p<0.001), but head CT was performed more frequently at night or on weekends/holidays(16.1% vs. 34.7%, p<0.001) There is low incidence of head trauma in the winter in children (p<0.001). In the multivariate logistic regression analysis, patients who were adults, female, or ED visitors were more likely to undergo brain CT (odds ratio (OR): 1.65, 95% confidence interval (CI): 1.47-1.84; OR: 1.40, 95% CI: 1.27-1.54; OR: 7.80, 95% CI: 6.91-8.80, respectively). Conclusion: In this study, we analyzed the national epidemiologic trend for head trauma, and the pattern of utilization of brain CT.
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