• Nuclear Medicine and Molecular Imaging
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• v.41 no.4
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• pp.337-338
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• 2007

A 20-year-old man underwent a Tc-99m HMPAO labeled leukocyte scan for the evaluation of an infection at the stump of an AK amputation, which was conducted due to an open communicated fracture of the left lower leg. Blood-flow and blood-pool images demonstrated a pseudoaneurysm with a focus of intense activity medial to the stump, and centered within a large photopenic defect by surrounding hematoma. Delayed image obtained at 3 hours post-injection showed persistent intense and slight increased activity, Contrast angiography confirmed the presence of a pseudoaneurysm arising from a branch of the left superficial femoral artery.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.301-303
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• 2002

Subspace analysis is a popular method for multivariate data analysis and is closely related to factor analysis and principal component analysis (PCA). In the context of image processing (especially positron emission tomography), all data points are nonnegative and it is expected that both basis images and factors are nonnegative in order to obtain reasonable result. In this paper We present a sequential EM algorithm for rectified subspace analysis (subspace in nonnegativity constraint) and apply it to dynamic PET image analysis. Experimental results show that our proposed method is useful in dynamic PET image analysis.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.1
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• pp.17-24
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• 2011

Purpose: Presently in the nuclear medicine field, the high-speed image reconstruction algorithm like the OSEM algorithm is widely used as the alternative of the filtered back projection method due to the rapid development and application of the digital computer. There is no to relate and if it applies the optimal parameter be clearly determined. In this research, the quality change of the Jaszczak phantom experiment and brain SPECT patient data according to the iteration times and subset number change try to be been put through and analyzed in 3D OSEM reconstruction method of applying 3D beam modeling. Materials and Methods: Patient data from August, 2010 studied and analyzed against 5 patients implementing the brain SPECT until september, 2010 in the nuclear medicine department of ASAN medical center. The phantom image used the mixed Jaszczak phantom equally and obtained the water and 99mTc (500 MBq) in the dual head gamma camera Symbia T2 of Siemens. When reconstructing each image altogether with patient data and phantom data, we changed iteration number as 1, 4, 8, 12, 24 and 30 times and subset number as 2, 4, 8, 16 and 32 times. We reconstructed in reconstructed each image, the variation coefficient for guessing about noise of images and image contrast, FWHM were produced and compared. Results: In patients and phantom experiment data, a contrast and spatial resolution of an image showed the tendency to increase linearly altogether according to the increment of the iteration times and subset number but the variation coefficient did not show the tendency to be improved according to the increase of two parameters. In the comparison according to the scan time, the image contrast and FWHM showed altogether the result of being linearly improved according to the iteration times and subset number increase in projection per 10, 20 and 30 second image but the variation coefficient did not show the tendency to be improved. Conclusion: The linear relationship of the image contrast improved in 3D OSEM reconstruction method image of applying 3D beam modeling through this experiment like the existing 1D and 2D OSEM reconfiguration method according to the iteration times and subset number increase could be confirmed. However, this is simple phantom experiment and the result of obtaining by the some patients limited range and the various variables can be existed. So for generalizing this based on this results of this experiment, there is the excessiveness and the evaluation about 3D OSEM reconfiguration method should be additionally made through experiments after this.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.1
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• pp.61-69
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• 2008

Purpose: Micro-pinhole SPECT system with conventional multiple-head gamma cameras has the advantage of high magnification factor for imaging of rodents. However, several geometric factors should be calibrated to obtain the SPECT image with good image quality. We developed a simplified geometric calibration method for rotating triple-head pinhole SPECT system and assessed the effects of the calibration using several phantom and rodent imaging studies. Materials and Methods: Trionix Triad XLT9 triple-head SPECT scanner with 1.0 mm pinhole apertures were used for the experiments. Approximately centered point source was scanned to track the angle-dependent positioning errors. The centroid of point source was determined by the center of mass calculation. Axially departed two point sources were scanned to calibrate radius of rotation from pinhole to center of rotation. To verify the improvements by the geometric calibration, we compared the spatial resolution of the reconstructed image of Tc-99m point source with and without the calibration. SPECT image of micro performance phantom with hot rod inserts was acquired and several animal imaging studies were performed. Results: Exact sphere shape of the point source was obtained by applying the calibration and axial resolution was improved. Lesion detectibility and image quality was also much improved by the calibration in the phantom and animal studies. Conclusion: Serious degradation of micro-pinhole SPECT images due to the geometric errors could be corrected using a simplified calibration method using only one or two point sources.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.2
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• pp.129-136
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• 2009

Purpose: To determine optimal imaging time for diagnostic I-123 whole body scan in the follow-up of patients with differentiated thyroid cancer(DTC), we compared the image quality of 6- and 24-hour images of the same subjects. Materials and Methods: Four hundred ninety-eight patients(M:F = 55:443, Age $47.6{\pm}12.9$ years) with DTC who had undergone total thyroidectomy and I-131 ablation therapy underwent diagnostic whole body scanning 6 hour and 24 hour after oral ingestion of 185 MBq(5 mCi) of I-123. Serum thyroglobulin measurement and ultrasonography of the neck were performed at the time of imaging. In 40 patients underwent additional I-131 therapy, post-therapy I-131 images were obtained and compared with diagnostic I-123 images. Results: In 440 patients(88.4%), 6- and 24-hour diagnostic I-123 images were concordant, and 58 patients(11.6%) showed discordant findings. Among 58 discordant patients, 31 patients showed abnormal tracer uptake on only 6-hour image, which turned out false-positive findings in all cases. In 12 patients with positive findings on only 24-hour image, remnant thyroid tissue(4 patients) and cervical lymph node metastasis(3 patients) were presented. Among 40 patients underwent additional I-131 therapy, 6-hour and 24-hour images were discordant in 13 patients. All 5 patients with abnormal uptake on only 6-hour image revealed false-positive results, whereas most of 24-hour images were concordant with post-therapy I-131 images. Conclusion: I-123 imaging at 24-hour could reduce false-positive findings and improve diagnostic accuracy, compared with 6-hour image in the follow-up of patient with DTC.

• The Korean Journal of Nuclear Medicine Technology
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• v.27 no.2
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• pp.129-132
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• 2023

Purpose: Positron emisson tomography (PET) is a crucial medical imaging scanner for the detection of cancer lesions. In order to maintain the improved image quality, it is crucial to apply detectors of superior performance. Therefore, the purpose of this study was to compare PET image quality using Monte Carlo simulation based on the detector materials of BGO, LSO, and LuAP. Materials and Methods: The Geant4 Application for Tomographic Emission (GATE) was used to design the PET detector. Scintillations with BGO, LSO and LuAP were modelled, with a size of 3.95 × 5.3 mm2 (width × height) and 25.0 mm (thickness). The PET detector consisted of 34 blocks per ring and a total of 4 rings. A line source of 1 MBq was modelled and acquired with a radius of 1 mm and length of 20 mm for 20 seconds. The acquired image was reconstructed maximum likelihood expectation maximization with 2 iteration and 10 subsets. The count comparison was carried out. Results and Discussion: The highest true, random, and scatter counts were obtained from the BGO scintillation detector compared to LSO and LuAP. Conclusion: The BGO scintillation detector material indicated excellent performance in terms of detection of gamma rays from emitted PET phantom.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2004.11a
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• pp.104-107
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• 2004

In this study, using brain phantom for multi-modality imaging, we acquired CT, MR and PET images and performed registration of these anatomical images and nuclear medicine functional images. The algorithms and program applied for registration were Chamfer Matching and Mutual Information Maximization algorithm which have been using frequently in clinic and verified accuracy respectively. In result, both algorithms were useful methods for CT-MR, CT-PET and MR-PET. But Mutual Information Maximization was more effective algorithm for low resolution image as nuclear medicine functional image.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.4
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• pp.328-332
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• 2008

Simple bone cyst (SBC) is very rare in adult ribs. The diagnosis basically relies on conventional radiography and occasionally on a. There has been no earlier publication on PET/CT diagnosis of SBC. We report a case of adult costal SBC diagnosed by positive $^{18}F$-fluorodeoxyglucose (FDG) uptake. Histology showed the FDG uptake to be associated with reactive woven bone formation and nonspecific chronic inflammation. Correlation of PET, CT, plain radiography and sonography are also described.

• Progress in Medical Physics
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• v.30 no.2
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• pp.49-58
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• 2019

Purpose: Automated analytical systems have begun to emerge as a database system that enables the scanning of medical images to be performed on computers and the construction of big data. Deep-learning artificial intelligence (AI) architectures have been developed and applied to medical images, making high-precision diagnosis possible. Materials and Methods: For diagnosis, the medical images need to be labeled and standardized. After pre-processing the data and entering them into the deep-learning architecture, the final diagnosis results can be obtained quickly and accurately. To solve the problem of overfitting because of an insufficient amount of labeled data, data augmentation is performed through rotation, using left and right flips to artificially increase the amount of data. Because various deep-learning architectures have been developed and publicized over the past few years, the results of the diagnosis can be obtained by entering a medical image. Results: Classification and regression are performed by a supervised machine-learning method and clustering and generation are performed by an unsupervised machine-learning method. When the convolutional neural network (CNN) method is applied to the deep-learning layer, feature extraction can be used to classify diseases very efficiently and thus to diagnose various diseases. Conclusions: AI, using a deep-learning architecture, has expertise in medical image analysis of the nerves, retina, lungs, digital pathology, breast, heart, abdomen, and musculo-skeletal system.

• The Korean Journal of Nuclear Medicine Technology
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• v.21 no.1
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• pp.29-33
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• 2017

Purpose In this study, we evaluated image by applying normalization factor during 30 days to the PET images. Materials and Methods Normalization factor was acquired during 30 days. We compared with 30 normalization factors. We selected 3 clinical case (PNS study). We applied for normalization factor to PET raw data and evaluated SUV and count (kBq/ml) by drawing ROI to liver and lesion. Results There is no significant difference normalization factor. SUV and count are not different for PET image according to normalization factor. Conclusion We can get a lot of information doing the quality assurance such as performance of sinogram and detector. That's why we need to do quality assurance daily.