• Annals of Clinical Neurophysiology
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• v.15 no.2
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• pp.42-47
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• 2013

Background: Diffusion-weighted image (DWI) might be useful to predict the prognosis of acute hypoxic encephalopathy. The aim of our study was to test whether the early change and extent of DWI abnormalities can be an indicator of the clinical outcome of hypoxic encephalopathy. Methods: Forty-four patients who were diagnosed as hypoxic encephalopathy due to the cardiorespiratory arrest were retrospectively identified. Clinical variables were determined, and the DWI abnormalities were counted by four areas: cortex, subcortical white matter, cerebellum and deep grey matter, and were divided into three groups by the extent of lesions. Prognosis was classified as 'poor' (Glasgow coma scale (GSC) at 30 days after arrest <9 or death) and 'good' (GSC at 30 days after arrest ${\geq}9$). Results: GCS at day 3 (p<0.001), presence of seizure (p=0.01), and presence of lesion (p<0.001) were significantly different in prognosis, but statistically there is no association with the extent of lesions and prognosis (p=0.26). Conclusions: Presence of early DWI changes could predict the clinical outcome of hypoxic encephalopathy after cardiorespiratory arrest.

• Investigative Magnetic Resonance Imaging
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• v.20 no.4
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• pp.241-249
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• 2016

Purpose: To evaluate the added value of diffusion weighted imaging (DWI) to computed tomography (CT) for detecting pancreatic abnormality in patients with clinically suspected acute pancreatitis (AP). Materials and Methods: 203 patients who underwent abdomen CT and subsequent DWI to do a workup for epigastric pain were analyzed. Two blinded radiologists independently performed an interval reading based on CT image sets first, then based on combined CT and DWI image sets. The diagnostic criterion on DWI was the increased signal intensity in the pancreas to that of the spleen. For quantitative analysis, the third radiologist measured ADC value of the pancreas in each patient. Results: For AP (n = 43), the sensitivity for detecting pancreatic abnormality increased, from 42% to 70% for reader 1 (P < 0.05) and from 44% to 72% for reader 2 (P < 0.05). For borderline pancreatitis (n = 42), the sensitivity also increased, from 10% to 26% for reader 1 (P < 0.05) and from 7% to 29% for reader 2 (P < 0.05). The mean ADC values (unit, ${\times}10^{-3}mm^2/s$) were significantly different among the three groups (for AP, $1.09{\pm}0.16$; for borderline pancreatitis, $1.28{\pm}0.2$; for control, $1.46{\pm}0.15$, P < 0.05). Conclusion: Sensitivity for detecting pancreatic abnormality increased significantly after adding DWI to CT in patients with clinically suspected AP.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4976-4994
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• 2018

The diffusion-based salient object detection methods have shown excellent detection results and more efficient computation in recent years. However, the current diffusion-based salient object detection methods still have disadvantage of detecting the object appearing at the image boundaries and different scales. To address the above mentioned issues, this paper proposes a multi-scale diffusion-based salient object detection algorithm with background and objectness seeds. In specific, the image is firstly over-segmented at several scales. Secondly, the background and objectness saliency of each superpixel is then calculated and fused in each scale. Thirdly, manifold ranking method is chosen to propagate the Bayessian fusion of background and objectness saliency to the whole image. Finally, the pixel-level saliency map is constructed by weighted summation of saliency values under different scales. We evaluate our salient object detection algorithm with other 24 state-of-the-art methods on four public benchmark datasets, i.e., ASD, SED1, SED2 and SOD. The results show that the proposed method performs favorably against 24 state-of-the-art salient object detection approaches in term of popular measures of PR curve and F-measure. And the visual comparison results also show that our method highlights the salient objects more effectively.

• Proceedings of the KSMRM Conference
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• 2005.09a
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• pp.27-27
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• 2005

• Progress in Medical Physics
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• v.21 no.1
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• pp.52-59
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• 2010

To examine among patients with vertebral compression fracture the extent to which signal-to-noise ratio (SNR) and Apparent Diffusion Coefficient (ADC) values at the lumbar vertebral compression fracture site vary on diffusion-weighted MR images according to varying b values on the 1.5T MR device. Diffusion-weighted MR images of 30 patients with compression fracture due to chronic osteoporosis who underwent vertebral MRI from Jan. 2008 to Nov. 2009 were respectively obtained using a 1.5-T MR scanner with the b values increased from 400, 600, 800, 1,000 to $1,200\;s/mm^2$. For diffusion-weighted MR images with different b values, the signal-to-noise ratio (SNR) was assessed at three sites: the site of compression fracture of the lumbar vertebral body at L1 to L5, and both the upper and lower discs of the said fracture site, while for ADC map images with different b values, the SNR and ADC were respectively assessed at those three sites. As a quantitative analysis, diffusion-weighted MR images and ADC map images with b value of $400\;s/mm^2$ (the base b values) were respectively compared with the corresponding images with each different b value. As far as qualitative analysis is concerned, for both diffusion-weighted MR and ADC map images with b value of $400\;s/mm^2$, the extent to which signal intensity values obtained at the site of compression fracture of the lumbar vertebral body at L1 to L5 vary according to the increasing b values were examined. The quantitative analysis found that for both diffusion-weighted MR and ADC map images, as the b values increased, the SNR were relatively lowered at all the three sites, compared to the base b value. Also, it was found that as the b values increased, ADC valueswere relatively lowered at all the three sites on ADC map images. On the other hand, the qualitative analysis found that as the b values increased to more than $400\;s/mm^2$, the signal intensity gradually decreased at all the sites, while at the levels of more than $1,000\;s/mm^2$, severe image noises appeared at all of the three sites. In addition, higher signal intensity was found at the site of compression fracture of the lumbar vertebral body than at the discs. Findings showed that with the b value being increased, both the signal-to-noise ratio (SNR) and Apparent Diffusion Coefficient (ADC) values gradually decreased at all the sites of the lumbar vertebral compression fracture and both the upper and lower discs of the fracture site, suggesting that there is a possibility of a wider range of applications to assessment of various vertebral pathologies by utilizing multi b values in the diffusion-weighted MRI examination.

• Investigative Magnetic Resonance Imaging
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• v.17 no.4
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• pp.312-315
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• 2013

When cerebral cortical hyperintensities on diffusion-weighted image are seen in patients with suspected acute stroke accompanying seizure, it is necessary to differentiate whether they are caused by infarction or seizure-related change. We report a case of seizure-related cortical hypertensities in a patient with suspected acute infarction. With perfusion MR imaging, we could differentiate from acute infarction.

• Biomedical Science Letters
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• v.10 no.2
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• pp.115-120
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• 2004

To investigate the correlation between the magnetic resonance imaging (MRI) of cerebral fat embolism that is induced by injecting oleic acid into 10 cats, and a pathologic diagnosis. Using a microcatheter, 30 ${mu}ell$ of oleic acid was injected into the internal carotid artery of 10 cats. MR T2-weighted image (T2WI), diffusion-weighted image (DWI) and Gadolinium-enhanced T1-weighted image (Gd-enhanced T1WI) were obtained after 30 minutes and 2 hours of embolization. After 30 minutes of the embolization, lesions of very high signal intensity were detected by T2WI in 6 cats, and of slightly high signal intensity in 2 cats; in the remaining 2 cats, signal intensity was normal. DWI showed lesions of very high intensity in 9 cats and of slightly high intensity in one cat. According to the findings of light microscopic examination, infarcted lesions mainly involved the gray matter, but also some white matter. A magnetic resonance imaging diagnosis for cerebral fat embolism that was induced by oleic acid through the internal carotid artery in cats showed high signal intensity on the T2WI and the DWI within an initial 2 hours, and with a well enhancement on the Gd-enhanced T1WI. Considering cellular edema, cerebrovascular injury and extracellular space widening, we assumed pathologically that cytotoxic and vasogenic edema exists at the same time.

• Investigative Magnetic Resonance Imaging
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• v.15 no.2
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• pp.102-109
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• 2011

Purpose : To retrospectively evaluate the usefulness of diffusion-weighted images, ADC maps and conventional MR images for determination of brain tumor consistency. Materials and Methods : Twenty-three patients with brain tumor underwent MR examinations with T1, T2 and diffusion-weighted images. Regions of interest (ROIs) were drawn in the tumors, and the measured signal intensities (SI) were normalized with the contralateral side. We evaluated the correlation between SI ratios from various images and tumor consistency assessed at surgery. In three patients with both cystic and solid components, each component was evaluated independently. Qualitatively observed SIs were also correlated with tumor consistency. Results : Statistical analysis revealed significant correlation between tumor consistency and ADC ratio (r = -0.586, p = 0.002), SI ratios on T2-weighted images (r = -0.497, p = 0.010), and observed SIs on T2-weighted images (r = -0.461, p = 0.018). The relative ratio of ADC value correlated with tumor consistency most strongly. Conclusion : The measured ratio of ADC, SI ratio and observed SI grade on T2-weighted images can provide valuable information about the consistency of brain tumor.

• Investigative Magnetic Resonance Imaging
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• v.25 no.2
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• pp.118-128
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• 2021

Purpose: To investigate the value of MR textural analysis, including use of diffusion-weighted imaging (DWI) to differentiate malignant from benign soft-tissue tumors on 3T MRI. Materials and Methods: We enrolled 69 patients (25 men, 44 women, ages 18 to 84 years) with pathologically confirmed soft-tissue tumors (29 benign, 40 malignant) who underwent pre-treatment 3T-MRI. We calculated MR texture, including mean, standard deviation (SD), skewness, kurtosis, mean of positive pixels (MPP), and entropy, according to different spatial-scale factors (SSF, 0, 2, 4, 6) on axial T1- and T2-weighted images (T1WI, T2WI), contrast-enhanced T1WI (CE-T1WI), high b-value DWI (800 sec/mm²), and apparent diffusion coefficient (ADC) map. We used the Mann-Whitney U test, logistic regression, and area under the receiver operating characteristic curve (AUC) for statistical analysis. Results: Malignant soft-tissue tumors had significantly lower mean values of DWI, ADC, T2WI and CE-T1WI, MPP of ADC, and CE-T1WI, but significantly higher kurtosis of DWI, T1WI, and CE-T1WI, and entropy of DWI, ADC, and T2WI than did benign tumors (P < 0.050). In multivariate logistic regression, the mean ADC value (SSF, 6) and kurtosis of CE-T1WI (SSF, 4) were independently associated with malignancy (P ≤ 0.009). A multivariate model of MR features worked well for diagnosis of malignant soft-tissue tumors (AUC, 0.909). Conclusion: Accurate diagnosis could be obtained using MR textural analysis with DWI and CE-T1WI in differentiating benign from malignant soft-tissue tumors.

• Journal of radiological science and technology
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• v.23 no.1
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• pp.39-47
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• 2000

In this study, we showed a comparison and analysis making use of DWI(diffusion weighted image) using early diagnosis of cerebral Infarction and with the classified T2 weighted image, FLAIR images signal intensity for brain infarction period. period of cerebral infarction after the condition of a disease by ischemic stroke. To compare 3 types of image, we performed polynomial warping and affined transform for image matching. Using proposed algorithm, calculated signal intensity difference between T2WI, DWI, FLAIR and DWI. The quantification values between hand made and calculated data are almost the same. We quantified the each period and performed pseudo color mapping by comparing signal intensity each other according to previously obtained hand made data, and compared the result of this paper according to obtained quantified data to that of doctors decision. The examined mean and standard deviation for each brain infarction stage are as follows ; the means and standard deviations of signal intensity difference between DWI and T2WI for each period are $197.7{\pm}6.9$ in hyperacute, $110.2{\pm}5.4$ in acute, and $67.8{\pm}7.2$ in subacute. And the means and standard deviations of signal intensity difference between DWI and FLAIR for each period are $199.8{\pm}7.5$ in hyperacute, $115.3{\pm}8.0$ in acute, and $70.9{\pm}5.8$ in subacute. We can quantificate and decide cerebral infarction period objectively. According to this study, DWI is very exact for early diagnosis. We classified the period of infarction occurrence to analyze the region of disease and normal region in DW, T2WI, FLAIR images.