• Imaging Science in Dentistry
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• v.44 no.3
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• pp.207-212
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• 2014

Purpose: This study aimed to investigate the deviation of landmarks from horizontal or midsagittal reference planes according to the methods of establishing reference planes. Materials and Methods: Computed tomography (CT) scans of 18 patients who received orthodontic and orthognathic surgical treatment were reviewed. Each CT scan was reconstructed by three methods for establishing three orthogonal reference planes (namely, the horizontal, midsagittal, and coronal reference planes). The horizontal (bilateral porions and bilateral orbitales) and midsagittal (crista galli, nasion, prechiasmatic point, opisthion, and anterior nasal spine) landmarks were identified on each CT scan. Vertical deviation of the horizontal landmarks and horizontal deviation of the midsagittal landmarks were measured. Results: The porion and orbitale, which were not involved in establishing the horizontal reference plane, were found to deviate vertically from the horizontal reference plane in the three methods. The midsagittal landmarks, which were not used for the midsagittal reference plane, deviated horizontally from the midsagittal reference plane in the three methods. Conclusion: In a three-dimensional facial analysis, the vertical and horizontal deviations of the landmarks from the horizontal and midsagittal reference planes could vary depending on the methods of establishing reference planes.

• The Journal of the Acoustical Society of Korea
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• v.28 no.2
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• pp.141-147
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• 2009

This paper presents a new fast algorithm, rotation-based method (RBM), for the reconstruction of 3 dimensional image for cone beam computerized tomography (CB CT) system. The system used cone beam has less exposure time of radioactivity than fan beam. The Three-Pass Shear Matrices (TPSM) is applied, that has less transcendental functions than the one-pass shear method to decrease a time of calculations in the computer. To evaluate the quality of the 3-D images and the time for the reconstruction of the 3-D images, another 3-D images were reconstructed by the radon transform under the same condition. For the quality of the 3-D images, the images by radon transform was shown little good quality than REM. But for the time for the reconstruction of the 3-D images REM algorithm was 35 times faster than radon transform. This algorithm offered $4{\sim}5$ frames a second. It meant that it will be possible to reconstruct the 3-D dynamic images in real time.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.6
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• pp.79-88
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• 1989

In this paper, linear octree is used to reconstruct and to modify the 3-dimensional image from 2-dimensional cross sections provided by computed tomography. Linear octree introduces a considerable data saving of the memory storage required by small computer system. This structure allows the hidden surface removal utilizing the spatial presortedness of hierarchical octree structure and implementation of graphical operations that include viewing transform and shading. An actual human organ is used to illustrate this technique and its implications for theraphy and surgical planning.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.591-597
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• 2012

Medical device performance has been advanced while images are expected to be acquired with further higher quality and pertinent applicability as images have been increasing in importance in analyzing major organs. Recent high frequency of image processing by MATLAB in image analysis area accounts for the intent of this study to segment pulmonary vessels by means of MATLAB. This study is to consist of 3 phases including pulmonary region segmentation, pulmonary vessel segmentation and three dimensional connectivity assessment, in which vessel was segmented, using threshold level, from the pulmonary region segmented, vessel thickness was measured as two dimensional refining process and three dimensional connectivity was assessed as three dimensional refining process. It is expected that MATLAB-based image processing should contribute to diversity and reliability of medical image processing and that the study results may lay a foundation for chest CT images-related researches.

• Clinics in Shoulder and Elbow
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• v.18 no.2
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• pp.86-90
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• 2015

Background: Although there are several methods for evaluating bone quality, Hounsfield units (HU), a standardized computed tomography (CT) attenuation coefficient, provide a useful tool for estimating focal bone mineral density (BMD). The aim of this study is to investigate the HU for evaluating the degree of osteoporosis in greater tuberosity with regard to anchor positioning. Methods: Forty patients diagnosed as normal on shoulder CT were included and categorized according to age and gender. Axially sectioned CT images were processed to 3-dimensional models containing information about bone quality using Mimics (14.11 platform v14.1.1.1 Materialise). Three-dimensional anchors were simulated and positioned according to 6 regions of interest (ROI) in the greater tuberosity classified using Tingart's system. Mean HU of intra-anchor volumes in the 6 regions was measured. Results: A significant decrease in HU was observed with increasing age (p=0.0001) and menopause (p<0.001). A significant difference in HU was found between male and female groups with males showing the higher values (p=0.0001). HU of proximal areas of ROI was higher than those of distal areas (p<0.005). However, although mean HU of distal posterior ROI showed the lowest values, no statistically significant difference was found between anterior, middle, and posterior regions (p=0.087). Conclusions: Mean HU of ROIs provides a tool for preoperative assessment of focal BMD, which is a factor of suture anchor stability and can be used to aid decision-making regarding secure anchor positioning for rotator cuff repair. Our data support that the most secure point is the proximal regions of ROI.

• Clinics in Shoulder and Elbow
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• v.23 no.3
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• pp.119-124
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• 2020

Background: This study was performed to compare glenoid version and inclination measured using two-dimensional (2D) images from computed tomography (CT) scans or three-dimensional (3D) reconstructed bone models. Methods: Thirty patients who had undergone conventional CT scans were included. Two orthopedic surgeons measured glenoid version and inclination three times on 2D images from CT scans (2D measurement), and two other orthopedic surgeons performed the same measurements using 3D reconstructed bone models (3D measurement). The 3D-reconstructed bone models were acquired and measured with Mimics and 3-Matics (Materialise). Results: Mean glenoid version and inclination in 2D measurements were -1.705° and 9.08°, respectively, while those in 3D measurements were 2.635° and 7.23°. The intra-observer reliability in 2D measurements was 0.605 and 0.698, respectively, while that in 3D measurements was 0.883 and 0.892. The inter-observer reliability in 2D measurements was 0.456 and 0.374, respectively, while that in 3D measurements was 0.853 and 0.845. Conclusions: The difference between 2D and 3D measurements is not due to differences in image data but to the use of different tools. However, more consistent results were obtained in 3D measurement. Therefore, 3D measurement can be a good alternative for measuring glenoid version and inclination.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.12
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• pp.205-212
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• 2003

Many people are exposed to accidents by vehicles or sports. The most frequent injuries by these accidents is concerned with a knee joint. The three-dimensional surface model of a knee is needed for dynamic analysis of knee motion and knee reconstruction. three-dimensional motion data of a knee joint were obtained using X-ray and precise magnetic sensors. The surface data of a femur and a tibia were obtained using cross-sectional pictures by CT. The three-dimensional surface models of a femur and a tibia were made by the method of optimal triangular patch. Using obtained motion data, we simulated the motion of three-dimensional knee joint model.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.27 no.4
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• pp.321-329
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• 2001

To establish systematic diagnosis and treatment planning of dentofacial deformity patient including facial asymmetry or hemifacial microsomia patient, comprehensive analysis of three dimensional structure of the craniofacial skeleton is needed. Even though three dimensional CT has been developed, landmark identification of the CT is still questionable. In recent, a method for correcting cephalic malpositioning that enables accurate superimposition of the landmarks in different stages without using any additional equipment was developed. It became possible to compare the three-dimensional positional change of the maxillomandible without invasive procedure. Based on the principle of the method, a new program was developed for the purpose of diagnosis and treatment planning of dentofacial deformity patient via three dimensional visualization and structural analysis. This program enables us to perform following menu. First, visualization of three dimensional structure of the craniofacial skeleton with wire frame model which was made from the landmarks observed on both lateral and frontal cephalogram. Second, establishment of midsagittal plane of the face three dimensionally, with the concept of "the plane of the best-fit". Third, examination of the degree of deviation and direction of deformity of structure to the reference plane for the purpose of establishing surgical planning. Fourth, simulation of expected postoperative result by various image operation such as mirroring, overlapping.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.10
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• pp.887-895
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• 2013

Metastatic bone cancer, the cancer which occurred in the various organs and progressively spread to bone, is one of the complications in cancer patients. This cancer is divided into the osteoblast and osteolytic metastasis. Although Computer Tomography(CT) could be an useful tool in diagnosis of bone metastasis, lesions are often missed by the visual inspection and it makes clinicians difficult to detect metastasis earlier. Therefore, in this study, we construct a three-dimensional(3D) volume rendering data from tomography images of the chest CT, and apply a 3D based image processing algorithm to them for detection bone metastasis lesions. Then we perform a three-dimensional visualization of the detected lesions.From our test using 10 clinical cases, we confirmed 94.1% of average sensitivity for osteoblast, and 90.0% of average sensitivity, respectively. Consequently, our findings showed a promising possibility and potential usefulness in diagnosis of metastastic bone cancer.

• Progress in Medical Physics
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• v.34 no.3
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• pp.23-32
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• 2023

Purpose: In radiomics analysis, to evaluate features, and predict genetic characteristics and survival time, the pixel values of lesions depicted in computed tomography (CT) and magnetic resonance imaging (MRI) images are used. CT and MRI offer three-dimensional images, thus producing three-dimensional features (Features_3d) as output. However, in reports, the superiority between Features_3d and two-dimensional features (Features_2d) is distinct. In this study, we aimed to investigate whether a difference exists in the prediction accuracy of radiomics analysis of lung cancer using Features_2d and Features_3d. Methods: A total of 38 cases of large cell carcinoma (LCC) and 40 cases of squamous cell carcinoma (SCC) were selected for this study. Two- and three-dimensional lesion segmentations were performed. A total of 774 features were obtained. Using least absolute shrinkage and selection operator regression, seven Features_2d and six Features_3d were obtained. Results: Linear discriminant analysis revealed that the sensitivities of Features_2d and Features_3d to LCC were 86.8% and 89.5%, respectively. The coefficients of determination through multiple regression analysis and the areas under the receiver operating characteristic curve (AUC) were 0.68 and 0.70 and 0.93 and 0.94, respectively. The P-value of the estimated AUC was 0.87. Conclusions: No difference was found in the prediction accuracy for LCC and SCC between Features_2d and Features_3d.