Tai-Been Chen

I-Shou University, Kao-hsiung-shih, Kaohsiung, Taiwan

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Publications (15)16.25 Total impact

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    ABSTRACT: State-of-the-art high resolution research tomography (HRRT) provides high resolution PET images with full 3D human brain scanning. But, a short time frame in dynamic study causes many problems related to the low counts in the acquired data. The PDS-OSEM algorithm was proposed to reconstruct the HRRT image with a high signal-to-noise ratio that provides accurate information for dynamic data. The new algorithm was evaluated by simulated image, empirical phantoms, and real human brain data. Meanwhile, the time activity curve was adopted to validate a reconstructed performance of dynamic data between PDS-OSEM and OP-OSEM algorithms. According to simulated and empirical studies, the PDS-OSEM algorithm reconstructs images with higher quality, higher accuracy, less noise, and less average sum of square error than those of OP-OSEM. The presented algorithm is useful to provide quality images under the condition of low count rates in dynamic studies with a short scan time.
    Radiation Physics and Chemistry 01/2014; 96:107–114. · 1.38 Impact Factor
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    ABSTRACT: This study evaluated and monitored the outcome of angiographic embolization of hepatic carcinoma by real-time C-arm angiographic computed tomography under number of tumors, size of tumors, and patient's age.METHODS AND MARTIALS: In total, 142 patients underwent angiographic embolization of hepatic carcinoma. The control group, 71 patients, underwent conventional angiographic (CA) embolization of hepatic carcinoma. The experimental group, 71 patients, underwent C-arm angiographic computed tomography (CCT) embolization of hepatic carcinoma. The numbers of angiographic embolization, number of tumors, size of tumors, and patients ages were recorded for comparisons between groups by analysis of variance (ANOVA) with cross-interaction and the chi-square test (cross table).
    Journal of X-Ray Science and Technology 01/2014; 22(5):645-51. · 1.09 Impact Factor
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    ABSTRACT: When using cardiac nuclear medicine images for diagnosis, the filtered back-projection (FBP) algorithm can reconstruct positron emission tomography (PET) images under low count rates. However, background strike artifacts in PET images are affected by diagnostic judgment. Hence, this study developed a robust method of removing background strike artifacts from FBP images without reducing image quality. A Jaszczak anthropomorphic torso phantom and a laboratory rabbit were used for performance tests of the proposed method. Parallel computing was applied to optimize the mask size of morphological structure operator (MSO) by minimizing the background standard deviation (Std). The optimal MSO mask size for the evaluated Jaszczak phantom was 3×3. The FBP images processed by MSO had significantly reduced strike artifacts measured by background Std (P=1E-5). After MSO processing, the time activity curve (TAC) of FBP images was stable and resembled the original FBP images (P=0.5). The proposed approach is highly stable and reduces noise by 13.08±2.32 in FBP images after MSO processing with 3×3 mask.
    Radiation Physics and Chemistry. 01/2014; 97:31–37.
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    ABSTRACT: The attenuation in ultrasound is one of primary factor reducing quality of image. The heterogeneity intensity of ultrasound images was made by scatter and attenuation. In this study, the quantitative analysis of liver ultrasound images was performed by three extracted features with and without depth corrections. A tissue phantom and 136 empirical images were involved to evaluate the reliability and performance with three extracted features. The average intensity of ROI with depth correction had better reliability and performance with AUC 0.689 and specificity, sensitivity, and accuracy are 67%, 60%, and 62% with respectively.
    Next-Generation Electronics (ISNE), 2013 IEEE International Symposium on; 01/2013
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    ABSTRACT: The function of left ventricle (LV) was evaluated by ejection fraction (EF) computed from minimum systolic and maximum diastolic phase CTA. The EF was took contrast enhanced of LV into consideration during phases of minimum systolic and maximum diastolic. In this study, the systolic volume ratio (sVr) was developed and used to analyze function of LV. The sVr was significant difference between positive and negative groups as well as EF. On the other hand, the sVr was high correlated with EF.
    Next-Generation Electronics (ISNE), 2013 IEEE International Symposium on; 01/2013
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    ABSTRACT: Most patients with liver cirrhosis must undergo a series of clinical examinations, including ultrasound imaging, liver biopsy, and blood tests. However, the quantification of liver cirrhosis by extracting significant features from a T2-weighted magnetic resonance image (MRI) provides useful diagnostic information in clinical tests. Sixty-two subjects were randomly selected to participate in this retrospective analysis with assigned to experimental and control groups. The T2-weighted MRI was obtained and to them dynamic adjusted gray levels. The extracted features of the image were standard deviation (SD), mean, and entropy of pixel intensity in the region of interest (ROI). The receiver operator characteristic (ROC) curve, 95% confidence intervals, and kappa statistics were used to test the significance and agreement. The analysis of area under ROC shows that SD, mean, and entropy in the ROI were significant between the experimental group and the control group. Smaller values of SD, mean, and entropy were associated with a higher probability of liver cirrhosis. The agreements between the extracted features and diagnostic results were shown significantly (P < 0.001). In this investigation, quantitative features of SD, mean, and entropy in the ROI were successfully computed by the dynamic gray level scaling of T2-weighted MRI with high accuracy.
    The Scientific World Journal 01/2012; 2012:343847. · 1.73 Impact Factor
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    ABSTRACT: Coronary artery calcification (CAC) scores are widely used to determine risk for Coronary Artery Disease (CAD). A CAC score does not have the diagnostic accuracy needed for CAD. This work uses a novel efficient approach to predict CAD in patients with low CAC scores. The study group comprised 86 subjects who underwent a screening health examination, including laboratory testing, CAC scanning, and cardiac angiography by 64-slice multidetector computed tomographic angiography. Eleven physiological variables and three personal parameters were investigated in proposed model. Logistic regression was applied to assess the sensitivity, specificity, and accuracy of when using individual variables and CAC score. Meta-analysis combined physiological and personal parameters by logistic regression. The diagnostic sensitivity of the CAC score was 14.3% when the CAC score was ≤30. Sensitivity increased to 57.13% using the proposed model. The statistically significant variables, based on beta values and P values, were family history, LDL-c, blood pressure, HDL-c, age, triglyceride, and cholesterol. The CAC score has low negative predictive value for CAD. This work applied a novel prediction method that uses patient information, including physiological and society parameters. The proposed method increases the accuracy of CAC score for predicting CAD.
    The Scientific World Journal 01/2012; 2012:907062. · 1.73 Impact Factor
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    ABSTRACT: Segmentation of positron emission tomography (PET) is typically achieved using the K-Means method or other approaches. In preclinical and clinical applications, the K-Means method needs a prior estimation of parameters such as the number of clusters and appropriate initialized values. This work segments microPET images using a hybrid method combining the Gaussian mixture model (GMM) with kernel density estimation. Segmentation is crucial to registration of disordered 2-deoxy-2-fluoro-D-glucose (FDG) accumulation locations with functional diagnosis and to estimate standardized uptake values (SUVs) of region of interests (ROIs) in PET images. Therefore, simulation studies are conducted to apply spherical targets to evaluate segmentation accuracy based on Tanimoto's definition of similarity. The proposed method generates a higher degree of similarity than the K-Means method. The PET images of a rat brain are used to compare the segmented shape and area of the cerebral cortex by the K-Means method and the proposed method by volume rendering. The proposed method provides clearer and more detailed activity structures of an FDG accumulation location in the cerebral cortex than those by the K-Means method.
    Journal of X-Ray Science and Technology 01/2012; 20(3):339-49. · 1.09 Impact Factor
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    ABSTRACT: Brown adipose tissue (BAT) is important for regulating body weight. Environmental temperature influences BAT activation. Activated BAT is identifiable using (18)F-fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-FDG PET/CT). (18)F-FDG PET/CT scans done between June 2005 and May 2009 in our institution in tropical southern Taiwan and BAT studies from PubMed (2002-2011) were reviewed, and the average outdoor temperatures during the study periods were obtained. A simple linear regression was used to analyze the association between the prevalence of activated BAT (P) and the average outdoor temperature (T). The review analysis for 9 BAT studies (n = 16, 765) showed a significant negative correlation (r = -0.741, P = 0.022) between the prevalence of activated BAT and the average outdoor temperature. The equation of the regression line is P(%) = 6.99 - 0.20 × T (°C). The prevalence of activated BAT decreased by 1% for each 5°C increase in average outdoor temperature. In a neutral ambient temperature, the prevalence of activated BAT is low and especially rare in the tropics. There is a significant linear negative correlation between the prevalence of activated BAT and the average outdoor temperature.
    The Scientific World Journal 01/2012; 2012:793039. · 1.73 Impact Factor
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    ABSTRACT: Brown adipose tissue (BAT) has thermogenic potential. For its activation, cold exposure is considered a critical factor though other determinants have also been reported. The purpose of this study was to assess the relationship between neoplastic status and BAT activity by 2-deoxy-2-[(18)F]fluoro-D-glucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) in people living in the tropics, where the influence of outdoor temperature was low. (18)F-FDG PET/CT scans were reviewed and the total metabolic activity (TMA) of identified activated BAT quantified. The distribution and TMA of activated BAT were compared between patients with and without a cancer history. The neoplastic status of patients was scored according to their cancer history and (18)F-FDG PET/CT findings. We evaluated the relationships between the TMA of BAT and neoplastic status along with other factors: age, body mass index, fasting blood sugar, gender, and outdoor temperature. Thirty of 1740 patients had activated BAT. Those with a cancer history had wider BAT distribution (p = 0.043) and a higher TMA (p = 0.028) than those without. A higher neoplastic status score was associated with a higher average TMA. Multivariate analyses showed that neoplastic status was the only factor significantly associated with the TMA of activated BAT (p = 0.016). Neoplastic status is a critical determinant of BAT activity in patients living in the tropics. More active neoplastic status was associated with more vigorous TMA of BAT.
    Lipids in Health and Disease 12/2011; 10:238. · 2.31 Impact Factor
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    ABSTRACT: Extending 32-bit DX generators introduced by Deng and Xu (ACM Trans Model Comput Simul 13:299–309, 2003), we perform an extensive computer search for classes of 64-bit and 128-bit DX generators of large orders. The period lengths of these high resolution DX generators are ranging from 101915 to 1058221. The software implementation of these generators can be developed for 64-bit or 128-bit hardware. The great empirical performances of DX generators have been confirmed by an extensive battery of tests in the TestU01 package. These high resolution DX generators can be useful to perform large scale simulations in scientific investigations for various computer systems.
    Computing 08/2010; 89:27-43. · 1.06 Impact Factor
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    ABSTRACT: The segmentation of cDNA microarray spots is essential in analyzing the intensities of microarray images for biological and medical investigation. In this work, nonparametric methods using kernel density estimation are applied to segment two-channel cDNA microarray images. This approach groups pixels into both a foreground and a background. The segmentation performance of this model is tested and evaluated with reference to 16 microarray data. In particular, spike genes with various contents are spotted in a microarray to examine and evaluate the accuracy of the segmentation results. Duplicated design is implemented to evaluate the accuracy of the model. The results of this study demonstrate that this method can cluster pixels and estimate statistics regarding spots with high accuracy.
    Journal of Biomedical Informatics 04/2008; 41(6):1021-7. · 2.13 Impact Factor
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    ABSTRACT: Positron emission tomography (PET) can provide in vivo, quantitative and functional information for diagnosis; however, PET image quality depends highly on a reconstruction algorithm. Iterative algorithms, such as the maximum likelihood expectation maximization (MLEM) algorithm, are rapidly becoming the standards for image reconstruction in emission-computed tomography. The conventional MLEM algorithm utilized the Poisson model in its system matrix, which is no longer valid for delay-subtraction of randomly corrected data. The aim of this study is to overcome this problem. The maximum likelihood estimation using the expectation maximum algorithm (MLE-EM) is adopted and modified to reconstruct microPET images using random correction from joint prompt and delay sinograms; this reconstruction method is called PDEM. The proposed joint Poisson model preserves Poisson properties without increasing the variance (noise) associated with random correction. The work here is an initial application/demonstration without applied normalization, scattering, attenuation, and arc correction. The coefficients of variation (CV) and full width at half-maximum (FWHM) values were utilized to compare the quality of reconstructed microPET images of physical phantoms acquired by filtered backprojection (FBP), ordered subsets-expected maximum (OSEM) and PDEM approaches. Experimental and simulated results demonstrate that the proposed PDEM produces better image quality than the FBP and OSEM approaches.
    Medical Engineering & Physics 08/2007; 30(6):680-6. · 1.78 Impact Factor
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    ABSTRACT: Positron emission tomography (PET) can reveal subtle metabolic process, which is an important modality for diagnosis. However, spatial resolution of PET images is not as good as computed tomo-graphy (CT) or magnetic resonance imaging (MRI), which can show precise anatomical details. Our study is to improve image quality of PET using better reconstruction methods. In this paper, we use a new and efficient method to incorporate the correlated structural information obtained from MRL A mean estimate smoothing the maximum likelihood estimate (MLE) locally within each region of inter-est is derived according to the boundaries provided by the structural information. Since the bounda-ries may not be correct, a penalized MLE using the mean estimate is sought. The resulting recon-struction is called a cross-reference maximum likelihood estimate (CRMLE). The CRMLE is obtained through a modified expectation maximization (EM) algorithm, which is shown to be computationally efficient by our phantom and clinical studies. Biomed Eng Appi Basis Comm, 2001 (February); 13: 1-7.
    Biomedical Engineering Applications Basis and Communications 01/2001; 13(01). · 0.23 Impact Factor
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    ABSTRACT: Iterative reconstruction (IR) algorithms can reduce artifacts caused by filtered backprojection (FBP) or convolution backprojection (CBP). Recently, the computational effects required for IR of positron emission tomography (PET) studies have been reduced to make it practically appealing. We have made an implementation of the improved maximum likelihood-expectation maximization (ML-EM) algorithm. The transition matrix was generated based on the geometry of the instrument. Phantoms of 6 line sources and 19 line sources were used to test our accelerated ML-EM algorithms against the FBP method. The singles were used to calculate the random coincidence rates by a well known formula and were compared to the randoms obtained by another geometric method. We also designed a new model using two line sources to determine the ratio of random events to true events. The artifacts near those line sources were eliminated with the ML-EM method. With decay correction, the RC events were uniformity distributed in whole field after 10 iterations. The ML-EM reconstructed images are superior to those obtained with FBP. The patterns of randoms provide insightful information for random correction, which the hardware correction by the delay window can not provide. This information is particularly valuable when the delay window correction is not available in the old fashion PET scanner.
    Proc SPIE 01/2000;