• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1248-1259
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• 2016

Classification methods based on dual energy X-ray absorptiometry, ultrasonic waves, and quantitative computed tomography have been proposed. Also, a classification method based on machine learning with bone mineral density and structural indicators extracted from the CT images has been proposed. We propose a method which enhances the performance of existing classification method based on bone mineral density and structural indicators by extending structural indicators and using principal component analysis. Experimental result shows that the proposed method in this paper improves the correctness of osteoporosis classification 2.8% with extended structural indicators only and 4.8% with both extended structural indicators and principal component analysis. In addition, this paper proposes a method of automatic phantom analysis needed to convert the CT values to BMD values. While existing method requires manual operation to mark the bone region within the phantom, the proposed method detects the bone region automatically by detecting circles in the CT image. The proposed method and the existing method gave the same conversion formula for converting CT value to bone mineral density.

• Journal of Yeungnam Medical Science
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• v.25 no.2
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• pp.108-116
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• 2008

Background : When surgeons plan mandible ortho surgery for patients with skeletal class III facial asymmetry, they must be consider the exact method of surgery for correction of the facial asymmetry. Three-dimensional (3D) CT imaging is efficient in depicting specific structures in the craniofacial area. It reproduces actual measurements by minimizing errors from patient movement and allows for image magnification. Due to the rapid development of digital image technology and the expansion of treatment range, rapid progress has been made in the study of three-dimensional facial skeleton analysis. The purpose of this study was to conduct 3D CT image comparisons of mandible changes after mandibular surgery in facial asymmetry patients. Materials & methods : This study included 7 patients who underwent 3D CT before and after correction of facial asymmetry in the oral and maxillofacial surgery department of Yeungnam University Hospital between August 2002 and November 2005. Patients included 2 males and 5 females, with ages ranging from 16 years to 30 years (average 21.4 years). Frontal CT images were obtained before and after surgery, and changes in mandible angle and length were measured. Results : When we compared the measurements obtained before and after mandibular surgery in facial asymmetry patients, correction of facial asymmetry was identified on the "after" images. The mean difference between the right and left mandibular angles before mandibular surgery was $7^{\circ}$, whereas after mandibular surgery it was $1.5^{\circ}$. The right and left mandibular length ratios subtracted from 1 was 0.114 before mandibular surgery, while it was 0.036 after mandibular surgery. The differences were analyzed using the nonparametric test and the Wilcoxon signed ranks test (p<0.05). Conclusion: The system that has been developed produces an accurate three-dimensional representation of the skull, upon which individualized surgery of the skull and jaws is easily performed. The system also permits accurate measurement and monitoring of postsurgical changes to the face and jaws through reproducible and noninvasive means.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.34 no.6
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• pp.622-627
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• 2008

In orthognathic surgery, precise analysis and diagnosis are essential for successful results. In facial asymmetric patient, traditional 2D image analysis has been used by lateral and P-A Cephalometric view, Skull PA, Panorama, Submentovertex view etc. But clinicians sometimes misdiagnose because they cannot find exact landmark due to superimposition, moreover image can be magnified and distorted by projection technique or patient's skull position, when using these analysis and method. For overcome these defects, analysis by using of 3D CT has been introduced. In this way we can analysis precisely by getting the exact image free of artifact and finding exact landmark with no interruption of superimposition. So we want to review of relationship between various skeletal landmarks of mandible or cranial base and facial asymmetry by predictable analysis using 3D CT. We select the cases of the patients who visited our department for correction of facial asymmetry during 2003-2007 and who were taken image of 3D CT for diagnosis. 3D CT images were reconstructed to 3D image by using V-Work program (Cybermed Inc., Seoul, Korea). And we analysis the relationship between facial asymmetry and various affecting factor of skeletal pattern. The mandibular ramus hight difference between right and left was most affecting factor that express facial asymmetry. And in this research, there was no relationship between cranial base and facial asymmetry. The angulation between facial midline and mandibular ramus divergency has significant relationship with facial asymmetry

• Korean Journal of Digital Imaging in Medicine
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• v.12 no.2
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• pp.127-132
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• 2010

In this study, the correlation among the changes of Modulation Transfer Function(MTF) in the noise and high-contrast resolution and the change of Contrast to noise ratio(CNR) in the low-contrast resolution will be examined to investigate the estimation of image quality according to the type of algorithms. The image data obtained by scanning American Association of Physicists in Medicine(AAPM) phantom was applied to each algorithm and the exposure condition of 120 kVp, 250 mAs, and then the CT number and noise were measured. The MTF curved line of the high-contrast resolution was calculated with Point Spread Function(PSF) by using the analysis program by Philips, resulting in 0.5 MTF, 0.1 MTF and 0.02 MTF respectively. The low-contrast resolution was calculated with CNR and the uniformity was measured to each algorithm. Since the measurement value for the uniformity of the equipment was below ${\pm}$ 5 HU, which is the criterion figure, it was found to belong to the normal range. As the algorithm got closer from soft to edge, the standard deviation of CT number increased, which indicates that the noise increased as well. As for MTF, 0.5 MTF, 0.1 MTF and 0.02 MTF were all sharp algorithms, and as the algorithm got closer from soft to edge, it was possible to distinguish more clearly with the naked eye. On the other hand, CNR gradually decreased, because the difference between the contrast hole CT number and the acrylic CT number was the same while the noise of hole increased.

• Journal of Radiation Industry
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• v.17 no.4
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• pp.385-390
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• 2023

The uterus, one of women's reproductive organs, is also closely related to women's health. Among them, hemorrhagic luteal cysts, one of the causes of pelvic pain that women often experience, were observed through CT and ultrasound, and the quality of images was evaluated through quantitative and qualitative evaluations. This study sought to find out whether the test method is more helpful to patients during CT and ultrasound. This study was conducted on 15 adolescent women and 15 adult women(21.31±3.45 average age). The equipment used for filming used EC3-10X (3~10 MHZ) and Philips Mx8000 iCT 256 among Endocavity Probes among Ecube Platinum. After setting a constant ROI on the cyst and the interface as a quantitative analysis method, SNR and CNR values were measured on a 5-point scale based on image quality, lesion clarity, image distortion, clarity of the interface, and motion artifacts (p<0.05). Independent t-test and Mann Whiteny U were performed, and the statistical program used was noted when SPSS (Version 22.0 for windows software package, Chicago, IL, USA) was statistically less than 0.05. Comparing the SNR and CNR values for this experiment, it can be seen that the SNR value was higher in the case of CT images(p<0.05). As a result of the qualitative evaluation, the quality of the image, the clarity of the lesion, the distortion of the image, the clarity of the interface, and the clarity of the boundary were measured on a 5-point scale based on the movement artifact. Comparing each score, CT images scored higher with a finer difference than ultrasound images(p<0.05). In conclusion, both test methods showed excellent results in finding the patient's lesions. However, in quantitative and qualitative evaluations, CT produced higher results in detecting lesions than ultrasound. However, for cyst tests that require continuous observation, ultrasonography, a non-invasive method that is advantageous for patients, will be clinically useful. Therefore, observing the patient's lesions by appropriately distributing these two test methods will provide optimal diagnostic information. These results will be useful for providing clinical basic data and educational materials to CT and US users in the future.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.175-176
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• 2006

The aim of the 3D medical imaging is to facilitate the creation of clinically usable image-based algorithm. Clinically usable imaging algorithm for image analysis requires a high degree of interaction to verify and correct results from registration algorithms, such as the Insight Toolkit (ITK) and the Visualization Toolkit (VTK) which are the class libraries. ITK provides segmentation algorithms and VTK has powerful 3D visualization. However, to apply those libraries to the medical images such as Computerized Tomography (CT), the algorithm based on the interactive construction and modification of data objects are necessary. In this paper we showed the 3D registration about mandibular premolar of human teeth acquired by micro-CT scanner. Also, we used the ITK to find the contour of pulp layer of premolar, furthermore, the 3D imaging was visualized with VTK designed to create one kind of view on the data of 3D visualization. Finally, we evaluated that the volume model of pulp layer would be useful for the tooth morphology in dental medicine.

• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.331-338
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• 2013

CT for follow-up visits because of liver disease, body mass index (BMI) and kVp according to the change of the image quality and radiation dose to evaluate for changes. March 2010 to June 2011 at Pusan P University Hospital, abdominal CT scans a patient BMI (Body Mass Index. Less BMI) index was less than 25 in the treatment of subjects had a 48-person Noise and SNR at 100kVp abdominal image is lager than the 120kVp image. CTDI volume value at by the analysis of the radiation dose is 4.47mGy(100kVp) and 9.01mGy(120kVp). So CTDIvol in 100kVp is smaller than CTDIvol in 120kVp(decrease by 44.1%). And, effective dose is 7.1mSv(100kVp) and 12.51mSv(120kVp). So effective dose in 100kVp is smaller than effective dose in 120kVp(decrease by 43%). Evaluation of image quality is that Unacceptable 0 person, Suboptimal 0 person, Adequate 0 person, Good 1 person, Excellent 47 person. In case of repeatly patient, we examinate abdomianl CT scan by using low kVp and body mass index less than 25. We can has good quality image and benefit of low radiation dose.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.843-849
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• 2023

This study attempted to determine the optimal algorithm after quantitatively analyzing noise, SNR, and CNR measurements by reconstructing four algorithms (Standard, Soft, Bone, and Detail) from head and neck CT images of patients who underwent implant surgery. As an analysis method, pixel values were calculated through the region of interest in the reconstructed image using the Image J program. For noise, SNR, and CNR, the region of interest was measured at the location of the pharynx, masseter muscle, and parotid gland in the image, and the mean and SD values were obtained. The values of SNR and CNR were calculated based on the given formula. As a result, the standard algorithm showed the lowest noise and the highest SNR. CNR was highest in the Soft algorithm, but showed no significant difference from the Standard algorithm. Therefore, it is believed that the Standard algorithm is the optimal algorithm for examining patients wearing intraoral implants in head and neck CT examinations. We hope that the data from this study will be used as basic data for image evaluation in head and neck CT examinations, and that the quality of images will be further improved through various algorithm changes. It is believed that this will be an opportunity to do so.

• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.313-322
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• 2021

Purpose: To find diagnostic image features, to compare diagnostic performance of multiphase CT versus gadoxetic acid disodium-enhanced MRI (GAD-MRI), and to evaluate the impact of analyzing Liver Imaging Reporting and Data System (LI-RADS) imaging features, for distinguishing combined hepatocellular-cholangiocarcinoma (CHC) from hepatocellular carcinoma (HCC). Materials and Methods: Ninety-six patients with pathologically proven CHC (n = 48) or HCC (n = 48), diagnosed June 2008 to May 2018 were retrospectively analyzed in random order by three radiologists with different experience levels. In the first analysis, the readers independently determined the probability of CHC based on their own knowledge and experiences. In the second analysis, they evaluated imaging features defined in LI-RADS 2018. Area under the curve (AUC) values for CHC diagnosis were compared between CT and MRI, and between the first and second analyses. Interobserver agreement was assessed using Cohen's weighted κ values. Results: Targetoid LR-M image features showed better specificities and positive predictive values (PPV) than the others. Among them, rim arterial phase hyperenhancement had the highest specificity and PPV. Average sensitivity, specificity, and AUC values were higher for MRI than for CT in both the first (P = 0.008, 0.005, 0.002, respectively) and second (P = 0.017, 0.026, 0.036) analyses. Interobserver agreements were higher for MRI in both analyses (κ = 0.307 for CT, κ = 0.332 for MRI in the first analysis; κ = 0.467 for CT, κ = 0.531 for MRI in the second analysis), with greater agreement in the second analysis for both CT (P = 0.001) and MRI (P < 0.001). Conclusion: Rim arterial phase hyperenhancement on GAD-MRI can be a good indicator suggesting CHC more than HCC. GAD-MRI may provide greater accuracy than CT for distinguishing CHC from HCC. Interobserver agreement can be improved for both CT and MRI by analyzing LI-RADS imaging features.

• Journal of Biomedical Engineering Research
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• v.44 no.5
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• pp.303-314
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• 2023

This study aimed to assess the practical feasibility of advanced deformable image registration (DIR) algorithms in radiotherapy by employing two distinct datasets. The first dataset included 14 4D lung CT scans and 31 head and neck CT scans. In the 4D lung CT dataset, we employed the DIR algorithm to register organs at risk and tumors based on respiratory phases. The second dataset comprised pre-, mid-, and post-treatment CT images of the head and neck region, along with organ at risk and tumor delineations. These images underwent registration using the DIR algorithm, and Dice similarity coefficients (DSCs) were compared. In the 4D lung CT dataset, registration accuracy was evaluated for the spinal cord, lung, lung nodules, esophagus, and tumors. The average DSCs for the non-learning-based SyN and NiftyReg algorithms were 0.92±0.07 and 0.88±0.09, respectively. Deep learning methods, namely Voxelmorph, Cyclemorph, and Transmorph, achieved average DSCs of 0.90±0.07, 0.91±0.04, and 0.89±0.05, respectively. For the head and neck CT dataset, the average DSCs for SyN and NiftyReg were 0.82±0.04 and 0.79±0.05, respectively, while Voxelmorph, Cyclemorph, and Transmorph showed average DSCs of 0.80±0.08, 0.78±0.11, and 0.78±0.09, respectively. Additionally, the deep learning DIR algorithms demonstrated faster transformation times compared to other models, including commercial and conventional mathematical algorithms (Voxelmorph: 0.36 sec/images, Cyclemorph: 0.3 sec/images, Transmorph: 5.1 sec/images, SyN: 140 sec/images, NiftyReg: 40.2 sec/images). In conclusion, this study highlights the varying clinical applicability of deep learning-based DIR methods in different anatomical regions. While challenges were encountered in head and neck CT registrations, 4D lung CT registrations exhibited favorable results, indicating the potential for clinical implementation. Further research and development in DIR algorithms tailored to specific anatomical regions are warranted to improve the overall clinical utility of these methods.