• Progress in Medical Physics
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• v.9 no.1
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• pp.47-53
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• 1998

Nuclear Medicine Images have comparatively poor spatial resolution, making it difficult to relate the functional information which they contain to precise anatomical structures. Anatomical structures useful in the interpretation of SPECT /PET Images were radiolabelled. PET/SPECT Images Provide functional information, whereas MRI mainly demonstrate morphology and anatomical. Fusion or Image Registration improves the information obtained by correlating images from various modalities. Brain Scan were studied on one or more occations using MRI and SPECT. The data were aligned using a point pair methods and surface matching. SPECT and MR Images was tested using a three dimensional water fillable Hoffman Brain Phantom with small marker and PET and MR Image was tested using a patient data. Registration of SPECT and MR Images is feasible and allows more accurate anatomic assessment of sites of abnormal uptake in radiolabeled studies. Point based registration was accurate and easily implemented three dimensional registration of multimodality data set for fusion of clinical anatomic and functional imaging modalities. Accuracy of a surface matching algorithm and homologous feature pair matching for three dimensional image registration of Single Photon Emission Computed Tomography Emission Computed Tomography (SPECT), Positron Emission Tomography (PET) and Magnetic Resonance Images(MRD was tested using a three dimensional water fill able brain phantom and Patients data. Transformation parameter for translation and scaling were determined by homologous feature point pair to match each SPECT and PET scan with MR images.

• Journal of radiological science and technology
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• v.39 no.2
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• pp.227-236
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• 2016

Dynamic positron emission tomography(dPET) is widely used medical imaging modality that can provide both physiological and functional neuro-image for diagnosing various brain disease. However, dPET images have low spatial-resolution and high noise level during spatio-temporal analysis (three-dimensional spatial information + one-dimensional time information), there by limiting clinical utilization. In order to overcome these issues for the spatio-temporal analysis, a novel computational technique was introduced in this paper. The computational technique based on singular value decomposition classifies multiple independent components. Signal components can be distinguished from the classified independent components. The results show that signal to noise ratio was improved up to 30% compared with the original images. We believe that the proposed computational technique in dPET can be useful tool for various clinical / research applications.

• The Korean Journal of Nuclear Medicine
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• v.32 no.4
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• pp.332-343
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• 1998

Purpose: The purpose of this study was to assess the diagnostic accuracy of various quantitation methods using F-18-fluorodeoxyglucose (FDG) in patients with malignant or benign lung lesion. Materials and Methods: 22 patients (13 malignant including 5 bronchoalverolar cell cancer; 9 benign lesions including 1 hamartoma and 8 active inflammation) were studied after overnight fasting. We performed dynamic PET imaging for 56 min after injection of 370 MBq (10 mCi) of FDG. Standardized uptake values normalized to patient's body weight and plasma glucose concentration (SUVglu) were calculated. The uptake rate constant of FDG and glucose metabolic rate were quantified using Patlak graphical analysis (Kpat and MRpat), three compartment-five parameter model (K5p, MR5p), and six parameter model taking into account heterogeneity of tumor tissue (K6p, MR6p). Areas under receiver operating characteristic curves (ROC) were calculated for each method. Results: There was no significant difference of rate constant or glucose metabolic rate measured by various quantitation methods between malignant and benign lesions. The area under ROC curve were 0.73 for SUVglu, 0.66 for Kpat, 0.77 for MRpat, 0.71 for K5p, 0.73 for MR5p, 0.70 for K6p, and 0.78 for MR6p. No significant difference of area under the ROC curve between these methods was observed except the area between Kpat vs. MRpat (p<0.05). Conclusion: Quantitative methods did not improve diagnostic accuracy in comparison with nonkinetic methods. However, the clinical utility of these methods needs to be evaluated further in patients with low pretest likelihood of active inflammation or bronchoalveolar cell carcinoma.

• The Korean Journal of Nuclear Medicine
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• v.31 no.1
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• pp.73-82
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• 1997

Regional myocardial blood flow (rMBF) can be noninvasively quantified using N-13 ammonia and dynamic positron emission tomography (PET). The quantitative accuracy of the rMBF values, however, is affected by the distortion of myocardial PET images caused by finite PET image resolution and cardiac motion. Although different methods have been developed to correct the distortion typically classified as partial volume effect and spillover, the methods are too complex to employ in a routine clinical environment. We have developed a refined method incorporating a geometric model of the volume representation of a region-of-interest (ROI) into the two-compartment N-13 ammonia model. In the refined model, partial volume effect and spillover are conveniently corrected by an additional parameter in the mathematical model. To examine the accuracy of this approach, studies were performed in 9 coronary artery disease patients. Dynamic transaxial images (16 frames) were acquired with a GE $Advance^{TM}$ PET scanner simultaneous with intravenous injection of 20 mCi N-13 ammonia. rMBF was examined at rest and during pharmacologically (dipyridamole) induced coronary hyperemia. Three sectorial myocardium (septum, anterior wall and lateral wall) and blood pool time-activity curves were generated using dynamic images from manually drawn ROIs. The accuracy of rMBF values estimated by the refined method was examined by comparing to the values estimated using the conventional two-compartment model without partial volume effect correction rMBF values obtained by the refined method linearly correlated with rMBF values obtained by the conventional method (108 myocardial segments, correlation coefficient (r)=0.88). Additionally, underestimated rMBF values by the conventional method due to partial volume effect were corrected by theoretically predicted amount in the refined method (slope(m)=1.57). Spillover fraction estimated by the two methods agreed well (r=1.00, m=0.98). In conclusion, accurate rMBF values can be efficiently quantified by the refined method incorporating myocardium geometric information into the two-compartment model using N-13 ammonia and PET.