• Investigative Magnetic Resonance Imaging
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• v.23 no.2
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• pp.148-156
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• 2019

Hyperglycemia-induced hemichorea (HGHC) is a rare but characteristic hyperkinetic movement disorder involving limbs on one side of the body. In a 75-year-old woman with a left-sided HGHC, conventional brain MR imaging showed very subtle T1-hyperintensity and unique gadolinium enhancement in the basal ganglia contralateral to movements. Multi-parametric MRI was acquired using pulse sequence with quantification of relaxation times and proton density by multi-echo acquisition. Myelin map was reconstructed based on new tissue classification modeling. In this case report of multi-parametric MRI, quantitative measurement of myelin change related to HGHC in brain structures and its possible explanations are presented. This is the first study to demonstrate myelin loss related to hyperglycemic insult in multi-parametric quantitative MR imaging.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5179-5196
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• 2019

To explore an effective non-invasion medical imaging diagnostics approach for hepatocellular carcinoma (HCC), we propose a method based on adopting the multiple technologies with the multi-parametric data fusion, transfer learning, and multi-scale deep feature extraction. Firstly, to make full use of complementary and enhancing the contribution of different modalities viz. multi-parametric MRI images in the lesion diagnosis, we propose a data-level fusion strategy. Secondly, based on the fusion data as the input, the multi-scale residual neural network with SPP (Spatial Pyramid Pooling) is utilized for the discriminative feature representation learning. Thirdly, to mitigate the impact of the lack of training samples, we do the pre-training of the proposed multi-scale residual neural network model on the natural image dataset and the fine-tuning with the chosen multi-parametric MRI images as complementary data. The comparative experiment results on the dataset from the clinical cases show that our proposed approach by employing the multiple strategies achieves the highest accuracy of 0.847±0.023 in the classification problem on the HCC differentiation. In the problem of discriminating the HCC lesion from the non-tumor area, we achieve a good performance with accuracy, sensitivity, specificity and AUC (area under the ROC curve) being 0.981±0.002, 0.981±0.002, 0.991±0.007 and 0.999±0.0008, respectively.

• Journal of Korea Multimedia Society
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• v.19 no.4
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• pp.736-746
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• 2016

In this paper, we propose an automatic prostate cancer detection method using position, signal intensity and texture feature based on SVM in multi-parametric MR images. First, to align the prostate on DWI and ADC map to T2wMR, the transformation parameters of DWI are estimated by normalized mutual information-based rigid registration. Then, to normalize the signal intensity range among inter-patient images, histogram stretching is performed. Second, to detect prostate cancer areas in T2wMR, SVM classification with position, signal intensity and texture features was performed on T2wMR, DWI and ADC map. Our feature classification using multi-parametric MR imaging can improve the prostate cancer detection rate on T2wMR.

• Investigative Magnetic Resonance Imaging
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• v.9 no.1
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• pp.30-35
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• 2005

Purpose : The purpose of this study is to observe the blood oxygen level dependent (BOLD) contrast changes due to the reaction of human brain at a gustatory sense in response to a salty-taste stimulation. Materials and Methods : Twelve healthy, non-smoking, right-handed male subjects (mean age: 25.6, range: 23-28 years) participated in this salty-taste stimulus functional magnetic resonance (fMRI) study. MRI scans were performed with 1.57 GE Signa, using a multi-slice GE-EPI sequence according to a blood-oxy-gen-level dependent (BOLD) experiment paradigm. Scan parameters included matrix size $128\times128$, FOV 250 mm, TR 5000 msec, TE 60 msec, TH/GAP 5/2 mm. Sequential data acquisitions were carried out for 42 measurements with a repetition time of 5 sec for each taste-stimulus experiments. Analysis of fMRI data was carried out using SPM99 implemented in Matlab. NaCl solution $(3\%)$ was used as a salty stimulus. The task paradigm consisted of alternating rest-stimulus cycles (30-second rest, 15-second stimulus) for 210 seconds. During the stimulus period, NaCl-solution was presented to the subject's mouth through plastic tubes as a bolus of delivered every 5 sec using -processor controlled auto-syringe pump. Results : Insula, frontal opercular taste cortex, amygdala and orbitofrontal cortex (OFC) were activated by a salty-taste stimulation $(NaCl,\;3\%)$ in the fMRI experiments. And dosolateral prefrontal cortex (DLPFC) was also significantly responded to salty-taste stimuli. Activation areas of the right side hemisphere were more superior to the left side hemisphere. Conclusion : The results of this study well correspond to the fact that both insula, amygdala, OFC, DLPFC areas are established as taste cortical areas by neuronal recordings in primates. Authors found that laboratory-developed auto-syringe pump is suitable for gustatory fMRI study. Further research in this field will accelerate to inquire into the mechanism of higher order gustatory process.