• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.18-23
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• 2010

Purpose: PET/CT combines functional and morphologic data and increases diagnostic accuracy in a variety of malignancies. Especially reconstructed Fusion PET/CT images or MIP (Maximum Intensity Projection) images from a 2-dimensional image to a 3-dimensional one are useful in visualization of the lesion. But in Fusion & MIP 3D reconstruction image, due to hot uptake by urine or urostomy bag, lesion is overlapped so it is difficult that we can distinguish the lesion with the naked eye. This research tries to improve a distinction by removing parts of hot uptake. Materials and Methods: This research has been conducted the object of patients who have went to our hospital from September 2008 to March 2009 and have a lot of urine of remaining volume as disease of uterus, bladder, rectum in the result of PET/CT examination. We used GE Company's Advantage Workstation AW4.3 05 Version Volume Viewer program. As an analysis method, set up ROI in region of removal in axial volume image, select Cut Outside and apply same method in coronal volume image. Next, adjust minimum value in Threshold of 3D Tools, select subtraction in Advanced Processing. It makes Fusion & MIP images and compares them with the image no using Region Cut Definition. Results: In Fusion & MIP 3D reconstruction image, it makes Fusion & MIP images and compares them by using Advantage Workstation AW4.3 05's Region Cut Subtraction, parts of hot uptake according to patient's urine can be removed. Distinction of lesion was clearly reconstructed in image using Region Cut Definition. Conclusion: After examining the patients showing hot uptake on account of volume of urine intake in bladder, in process of reconstruction image, if parts of hot uptake would be removed, it could contribute to offering much better diagnostic information than image subtraction of conventional method. Especially in case of disease of uterus, bladder and rectum, it will be helpful for qualitative improvement of image.

• The Korean Journal of Nuclear Medicine Technology
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• v.17 no.1
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• pp.71-75
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• 2013

Purpose: Currently, decrement revision using LDCT is used in PET/CT. But cold artifacts are often found in decrement revision image by mismatch between LDCT image and Emission image near diaphragm due to patient's respiration. This research studied reduction of cold artifact by patient's respiration using CTAC Shift among revision methods. Materials and Methods: From March to September in 2012, 30 patients who had cold artifacts by respiration were targeted using PET/CT Discovery 600 (GE Healthcare, MI, USA) equipment. Patients with cold artifacts were additionally scan in diaphragm area, and the image shown cold artifacts at whole body test were revised using CTAC Shift. Cold artifacts including image, additional scan image and CTAC Shift revision image were evaluated as 1~5 points with naked eye by one nuclear medicine expert, 4 radiotechnologists with over 5 year experience. Also, standard uptake value of 3 images was compared using paired t-test. Results: Additional scan image and CTAC Shift revision image received relatively higher score in naked eye evaluation than cold artifacts including image. The additional scan image and CTAC Shift revision image had high correlation as the results of ANOVA test of standard uptake value and did not show significant difference. Conclusion: When cold artifacts are appeared by patient's respiration at PET/CT, it causes not only patient inconvenience but troubles in test schedule due to extra radiation exposure and time consumption by additional scan. But if CTAC Shift revision image can be acquired with out additional scan, it is considered to be helped in exact diagnosis without unnecessary extra radiation exposure and additional scan.

• Progress in Medical Physics
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• v.23 no.4
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• pp.309-316
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• 2012

Multimodal-imaging technique has been rapidly developed for improvement of diagnosis and evaluation of therapeutic effects. In despite of integrated hardware, registration accuracy was decreased due to a discrepancy between multimodal image and insufficiency of count in accordance with different acquisition method of each modality. The purpose of this study was to improve the PET image by event data resampling through analysis of data format, noise and statistical properties of small animal PET list data. Inveon PET listmode data was acquired as static data for 10 min after 60 min of 37 MBq/0.1 ml $^{18}F$-FDG injection via tail vein. Listmode data format was consist of packet containing 48 bit in which divided 8 bit header and 40 bit payload space. Realigned sinogram was generated from resampled event data of original listmode by using adjustment of LOR location, simple event magnification and nonparametric bootstrap. Sinogram was reconstructed for imaging using OSEM 2D algorithm with 16 subset and 4 iterations. Prompt coincidence was 13,940,707 count measured from PET data header and 13,936,687 count measured from analysis of list-event data. In simple event magnification of PET data, maximum was improved from 1.336 to 1.743, but noise was also increased. Resampling efficiency of PET data was assessed from de-noised and improved image by shift operation of payload value of sequential packet. Bootstrap resampling technique provides the PET image which noise and statistical properties was improved. List-event data resampling method would be aid to improve registration accuracy and early diagnosis efficiency.

• Applied Chemistry for Engineering
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• v.25 no.1
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• pp.14-19
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• 2014

Nanocomposites based on poly(methyl methacrylate) (PMMA)/poly(vinylidene fluoride) (PVDF) and poly(ethylene terephthalate) (PET)/(PVDF) blended with carbon fibers (CF) and carbon nanotube (CNT) were prepared by melt mixing in the twin screw extruder. Morphologies of the PMMA/PVDF/CF/CNT and PET/PVDF/CF/CNT nanocomposites were investigated using SEM. The aggregation of CNT was observed in PMMA/PVDF/CF/CNT nanocomposites while the good dispersion of CNT was shown in PET/PVDF/CF/CNT nanocomposites. In SEM image of PET/PVDF/CF/CNT nanocomposite, the CNT were mainly located at the PET domain of phase-separated PET/PVDF blend due to the ${\pi}-{\pi}$ interaction between the phenyl ring of PET and graphite sheet of the CNT's surface. In addition, a fairly good compatibility between PET/PVDF matrix and CF was shown in the SEM image. In the case of PET/PVDF nanocomposites blended with the co-addition of CF and CNT, the volume electrical resistivity decreased while no change was observed in PMMA/PVDF/CF/CNT composites. The degree of CNT dispersion in morphology results was consistent with the electrical conductivity results. From the DSC results, the crystallization temperature (Tc) of PET/PVDF/CF/CNT nanocomposites increased due to the co-addition of CF and CNTs acting as a nucleating agent. Flexural modulus of PET/PVDF/CF/CNT were sharply enhanced due to increasing the interaction between PET and CF.

• Journal of Radiation Industry
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• v.12 no.4
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• pp.267-276
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• 2018

A Hoffman 3D Brain Phantom was used to evaluate two PET/CT scanners, BIO_40 and D_690, according to the radiation dose of CT (low, medium and high) at a fixed kilo-voltage-peak (kVp) with the tube current(mA) varied in 17~20 stages(Bio_40 PET/CT scanner: the tube voltage was fixed to 120 kVp, the effective tube current(mAs) was increased from 33 mAs to 190 mAs in 10 mAs increments, D_690 PET/CT scanner: the tube voltage was fixed to 140 kVp, tube current(mA) was increased from 10 mAs to 200 mAs in 10 mAs increments). After obtaining the PET image, an attenuation correction was conducted based on the attenuation map, which led to an analysis of the difference in the image. First, the ratio of white to gray matter for each scanner was examined by comparing the coefficient of variation (CV) depending on the average ratio. In addition, a blind test was carried out to evaluate the image. According to the study results, the BIO_40 and D_690 scanners showed a <1% change in CV value due to the tube current conversion. The change in the coefficients of white and gray matter showed that the Z value was negative for both scanners, indicating that the coefficient of gray matter was higher than that of white matter. Moreover, no difference was observed when the images were compared in a blind test.

• Biomedical Science Letters
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• v.25 no.1
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• pp.99-106
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• 2019

Amyloid positron emission tomography (PET) allows early and accurate diagnosis in suspected cases of Alzheimer's disease (AD) and contributes to future treatment plans. In the present study, a method of implementing a diagnostic system to distinguish ${\beta}$-Amyloid ($A{\beta}$) positive from $A{\beta}$ negative with objectiveness and accuracy was proposed using a machine learning approach, such as the Principal Component Analysis (PCA) and Support Vector Machine (SVM). $^{18}F$-Florbetaben (FBB) brain PET images were arranged in control and patients (total n = 176) with mild cognitive impairment and AD. An SVM was used to classify the slices of registered PET image using PET template, and a system was created to diagnose patients comprehensively from the output of the trained model. To compare the per-slice classification, the PCA-SVM model observing the whole brain (WB) region showed the highest performance (accuracy 92.38, specificity 92.87, sensitivity 92.87), followed by SVM with gray matter masking (GMM) (accuracy 92.22, specificity 92.13, sensitivity 92.28) for $A{\beta}$ positivity. To compare according to per-subject classification, the PCA-SVM with WB also showed the highest performance (accuracy 89.21, specificity 71.67, sensitivity 98.28), followed by PCA-SVM with GMM (accuracy 85.80, specificity 61.67, sensitivity 98.28) for $A{\beta}$ positivity. When comparing the area under curve (AUC), PCA-SVM with WB was the highest for per-slice classifiers (0.992), and the models except for SVM with WM were highest for the per-subject classifier (1.000). We can classify $^{18}F$-Florbetaben amyloid brain PET image for $A{\beta}$ positivity using PCA-SVM model, with no additional effects on GMM.

• Journal of Korea Multimedia Society
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• v.8 no.12
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• pp.1565-1571
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• 2005

Images reconstructed with Maximum-Likelihood Expectation-Maximization (MLEM) algorithm have been observed to have checkerboard effects and have noise artifacts near edges as iterations proceed. To compensate this ill-posed nature, numerous penalized maximum-likelihood methods have been proposed. We suggest a simple algorithm of applying edge detecting process to the MLEM and Bayesian Expectation-Maximization (BEM) to reduce the noise artifacts near edges and remove checkerboard effects. We have shown by simulation that this algorithm removes checkerboard effects and improves the clarity of the reconstructed image and has good properties based on root mean square error (RMS).

• Journal of the Korean Society of Radiology
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• v.15 no.6
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• pp.891-897
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• 2021

With the development of Amyloid PET Tracer, the accuracy of Alzheimer's diagnosis can be improved through the identification of beta-amyloid neurites. However, the long image acquisition time of 20 minutes can be difficult for the patient. PET/CT scans are sensitive to patient movement and may partially affect test results. In this study, we studied the proper image acquisition time without affecting the quantitative evaluation of the image through the list mode acquisition method according to the time of the distribution of radioactive drugs in the body. The list mode includes information about time compared to the existing frame mode, and it is easy to analyze data because it can reconstruct images about the time that researchers want. The research method obtained a reconstructed image by time using a list mode of 5min frame/bed, 10min frame/bed, 15min frame/bed, and 20min frame/bed to compare the difference between signal-to-pons take ratio (SNR) and lesion-to-pons uptake ratio (LPR) and the difference in reading time to obtain an appropriate image. As a result of quantitative analysis, when measuring in list mode, SUVmean values decreased in 6 regions of interest as the image acquisition time increased, but showed the largest difference in 5 min/bed images, followed by 10 min/bed and 15 min/bed. As a result, the difference in SUVmean values decreased. Therefore, it was found that SUVmean values at 15 min/bed did not differ enough to not affect image evaluation. There was no difference in LPR values. As a result of the qualitative analysis, there was no change in the reading findings according to the PET image acquisition time and there was no significant difference in the qualitative analysis score of the image reconstruction according to time. As a result of the study, there is no significant difference between 15 min/bed and 20 min/bed images during the ¹⁸F-flutemetamol PET/CT test, so it can be said that it is clinically useful to reduce the image acquisition time selectively using 15 min/bed via list mode depending on the patient's condition.

• 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.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.433-440
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• 2018

Recently, MTV(metabolic tumor volume) has been used as indices of the whole tumor FDG uptake on FDG PET image but it is influenced by image reconstruction. The purpose of this study was to evaluate the correlation between actual volume and metabolic tumor volume applying different SUVmax threshold for different reconstruction algorithm on phantom study. Measurement were performed on a Siemens Biograph mCT40 using a NEMA IEC body phantom containing different size six spheres filled with F18-FDG applying four SBRs (4:1, 8:1, 10:1, 20:1). Images reconstructed four algorithms (OSEM3D, OSEM3D+PSF, OSEM3D +TOF, OSEM3D+TOF+PSF) and MTV were measured with different SUVmax threshold. Overall, the use of increasing thresholds result in decreasing MTV. and increasing the signal to background ratio decreased MTV by applying same SUVmax threshold. The 40% SUVmax threshold gave the best concordance between measured and actual volume in PSF and PSF+TOF reconstruction image. and the 45% threshold had the best correlation between the volume measured and actual volume in OSEM3D and TOF reconstruction image. we believe that this study will be used when the measurement of MTV applying various reconstruction image.