• Health Policy and Management
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• v.31 no.3
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• pp.261-271
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• 2021

Background: In 2018, the government increased the fee for the magnetic resonance imaging (MRI) image deciphering services of the external hospital to discourage the redundant MRI scan and to induce appropriate use of the MRI services. It is important to evaluate the effect of the policy to provide the basis for establishing other MRI-related policies. Methods: The healthcare data of the patients who had brain MRI scans were organized by episode and analyzed using the panel study in order to find out the effect of the MRI-related policy on the substitution effect and the medical expenses. Results: As a result of the increase in the fee of deciphering the MRI image, there has been an uplift in deciphering the MRI scan of the external hospital. It implies that more hospitals chose to use the MRI scan taken by other clinics or hospitals, rather than the MRI scan taken at their own facilities. Conclusion: The research results imply that a policy that facilitates the exchange of the medical image data between the hospitals is needed in order to establish an efficient management system of the healthcare resources. Such improvement is expected to reduce the social cost and contribute to the stability in the finance of national health insurance.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2197-2204
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• 2015

In recent years, medical image diagnosis has growing significant momentous in the medicinal field. Brain and lung image of patient are distorted with salt and pepper noise is caused by moving the head and chest during scanning process of patients. Reconstruction of these images is a most significant field of diagnostic evaluation and is produced clearly through techniques such as linear or non-linear filtering. However, restored images are produced with smaller amount of noise reduction in the presence of huge magnitude of salt and pepper noises. To eliminate the high density of salt and pepper noises from the reproduction of images, a new efficient fuzzy based median filtering algorithm with a moderate elapsed time is proposed in this paper. Reproduction image results show enhanced performance for the proposed algorithm over other available noise reduction filtering techniques in terms of peak signal -to -noise ratio (PSNR), mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), image enhancement factor (IMF) and structural similarity (SSIM) value when tested on different medical images like magnetic resonance imaging (MRI) and computer tomography (CT) scan brain image and CT scan lung image. The introduced algorithm is switching filter that recognize the noise pixels and then corrects them by using median filter with fuzzy two-sided π- membership function for extracting the local information.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.11-18
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• 2016

Magnetic resonance image (MRI) is widely used in brain research field and medical image. Especially, non-invasive brain activation acquired image technique, which is functional magnetic resonance image (fMRI) is used in brain study. In this study, we investigate brain activation occurred by LED light stimulation. For investigate of brain activation in experimental small animal, we used high magnetic field 9.4T MRI. Experimental small animal is Balb/c mouse, method of fMRI is using echo planar image (EPI). EPI method spend more less time than any other MRI method. For this reason, however, EPI data has low contrast. Due to the low contrast, image pre-processing is very hard and inaccuracy. In this study, we planned the study protocol, which is called block design in fMRI research field. The block designed has 8 LED light stimulation session and 8 rest session. All block is consist of 6 EPI images and acquired 1 slice of EPI image is 16 second. During the light session, we occurred LED light stimulation for 1 minutes 36 seconds. During the rest session, we do not occurred light stimulation and remain the light off state for 1 minutes 36 seconds. This session repeat the all over the EPI scan time, so the total spend time of EPI scan has almost 26 minutes. After acquired EPI data, we performed the analysis of this image data. In this study, we analysis of EPI data using statistical parametric map (SPM) software and performed image pre-processing such as realignment, co-registration, normalization, smoothing of EPI data. The pre-processing of fMRI data have to segmented using this software. However this method has 3 different method which is Gaussian nonparametric, warped modulate, and tissue probability map. In this study we performed the this 3 different method and compared how they can change the result of fMRI analysis results. The result of this study show that LED light stimulation was activate superior colliculus region in mouse brain. And the most higher activated value of segmentation method was using tissue probability map. this study may help to improve brain activation study using EPI and SPM analysis.

• Journal of the Korean Society of Radiology
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• v.15 no.1
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• pp.9-14
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• 2021

Recently, magnetic resonance imaging (MRI), which can acquire images with good contrast without exposure to radiation, has been widely used for diagnosis. However, noise that reduces the accuracy of diagnosis is essentially generated when acquiring the MR images, and by adjusting the parameters, the noise problem can be solved to obtain an image with excellent characteristics. Among the parameters, the number of excitation (NEX) can acquire images with excellent characteristics without additional degradation of image characteristics. In contrast, appropriate NEX setting is required since the scan time increases and motion artifacts may occur. Therefore, in this study, after fixing all MRI parameters through the MRiLab simulation program, we tried to evaluate the tendency of image characteristics according to changing NEX through quantitative evaluation of brain T2 weighted images acquired by adjusting only NEX. To evaluate the noise level and similarity of the acquired image, signal to noise ratio (SNR), contrast to noise ratio (CNR), root mean square error (RMSE) and peak signal to noise ratio (PSNR) were calculated. As a result, both noise level and similarity evaluation factors showed improved values as NEX increased, while the increasing width gradually decreased. In conclusion, we demonstrated that an appropriate NEX setting is important because an excessively large NEX does not affect image characteristics improvement and cause motion artifacts due to a long scan.

• Brain Tumor Research and Treatment
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• v.6 no.2
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• pp.68-72
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• 2018

We report a rare case of arachnoid granulations mimicking multiple osteolytic bone lesions. A 66-year-old woman was admitted to a local clinic for a regular checkup. Upon admission, brain CT showed multiple osteolytic lesions in the occipital bone. These needed to be differentiated from multiple osteolytic bone tumor. Subsequent brain MRI revealed that the osteolytic lesions were isointense to cerebrospinal fluid, hyperintense on T2-weighted image, hypointense on T1-weighted image, and with subtle capsules around the osteolytic lesions that were visible after gadolinium injection. A bone scan revealed no radiotracer uptake. The lesions were in both the transverse sinuses and the torcular herophili. With typical radiological appearances of the lesions, the osteolytic lesions were diagnosed as multiple arachnoid granulations. No further treatment was planned. A 1-year follow-up brain CT scan revealed no change. We should consider the possibility of arachnoid granulations when multiple osteolytic lesions are observed in the occipital bone.

• Journal of Radiation Industry
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• v.11 no.3
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• pp.139-144
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• 2017

To evaluation of clinical usefulness for B1+RMS limits, we compared image quality of Routine, Specific absorption rate (SAR) and Root mean square (RMS) protocol. 5 volunteers underwent Magnetic Resonance Imaging (MRI) scan of the brain using three different protocols. We draw Region of interest ROI in cortex, white matter, gray matter, putamen and thalamus of axial plan. Signal to noise ratio (SNR) were evaluated in each area and Contrast to noise ration (CNR) were evaluated between white matter and gray matter. Qualitative evaluation was used to score each ROI. B1+RMS is confirmed its usefulness compared to conventional SAR standard on the aspect of improvement of image quality, reduction of scan time and easy adjusting parameter.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.178-185
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• 2021

Three-dimensional high-resolution magnetic resonance imaging (MRI) provides fine-level anatomical information for disease diagnosis. However, there is a limitation in obtaining high resolution due to the long scan time for wide spatial coverage. Therefore, in order to obtain a clear high-resolution(HR) image in a wide spatial coverage, a super-resolution technology that converts a low-resolution(LR) MRI image into a high-resolution is required. In this paper, we propose a super-resolution technique through filter learning based on information on the surrounding gradient information in 3D space from 3D MRI images. In the learning step, the gradient features of each voxel are computed through eigen-decomposition from 3D patch. Based on these features, we get the learned filters that minimize the difference of intensity between pairs of LR and HR images for similar features. In test step, the gradient feature of the patch is obtained for each voxel, and the filter is applied by selecting a filter corresponding to the feature closest to it. As a result of learning 100 T1 brain MRI images of HCP which is publicly opened, we showed that the performance improved by up to about 11% compared to the traditional interpolation method.

• 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.

• Investigative Magnetic Resonance Imaging
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• v.4 no.2
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• pp.113-119
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• 2000

Purpose : To know the possibility of clinical application of MRI using oxygen inhalation as a perfusion MRI Materials and methods : Two healthy volunteers and three patients of one moyamoya disease, one acute infarction and one meningioma were studied using a 1.5 Tesla MRI unit. Oxygen (15 liters/min) mixed with room air was given using face mask from 8 second to 35 second during the study. Images were acquired 25 times (scan time per study were 1.6 seconds) using susceptibility contrast EPI (echo planar image) sequence. Difference maps were acquired by early (study 12-18), and late (study 19-25) O2 inhalation image groups minus pre-O2 inhalation image group (study 3-9) with a Z-score of 0.7-1.0 using VB31C program of Magneton Vision. The resulting perfusion images were created by superimposition of difference maps on corresponding T1 weighted anatomic images. On moyamoya patient, similar perfusion images were acquired after Gd-DTPA injection, and compared with O2 inhalation perfusion images. Results ; The author can get the perfusion images of the brain by oxygen inhalation with susceptibility contrast EPI sequence at the volunteers, and the patient of moyomoya disease, acute infarction and meningioma. On moyamoya patient, perfusion images with O2 inhalation are similar with perfusion images by Gd-DTPA injection. Conclusion 1 This study has demonstrated that the susceptibility contrast EPI by oxygen inhalation can be used as the clinically useful perfusion MRI technique

• Investigative Magnetic Resonance Imaging
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• v.14 no.1
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• pp.56-63
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• 2010

Purpose : DIR image is relatively free from susceptibility artifacts therefore, DIR image can make it possible to reliably measure cortical thickness/volume. One drawback of the DIR acquisition is the long scan time to acquire the fully sampled 3D data set. To solve this problem, we applied a parallel imaging method (GRAPPA) and verify the reliability of using the volumetric study. Materials and methods : Six healthy volunteers (3 males and 3 females; age $25.33{\pm}2.25$ years) underwent MRI using the 3D DIR sequence at a 3.0T Siemens Tim Trio MRI scanner. GRAPPA simulation was performed from the fully sampled data set for reduction factor 2. Data reconstruction was performed using MATLAB R2009b. Freesurfer v.4.3.0 was used to evaluate the cortical thickness of the entire brain, and to extract white matter information from the DIR image, Analyze 9.0 was used. The global cortical thickness estimated from the reconstructed image was compared with reference image by using a T-test in SPSS. Results : Although reduced SNR and blurring are observed from the reconstructed image, in terms of segmentation the effect was not so significant. The volumetric result was validated that there were no significant differences in many cortical regions. Conclusion : This study was performed with DIR image for a volumetric MRI study. To solve the long scan time of 3D DIR imaging, we applied GRAPPA algorithm. According to the results, fast imaging can be done with reduction factor 2 with little loss of image quality at 3.0T.