• Proceedings of the KSMRM Conference
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• 2001.11a
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• pp.112-112
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• 2001

Purpose： We developed the software for diffusion tensor imaging and evaluated its feasibility in norm brains. Method： Five normal volunteers, aged from 25 to 29 years, were examined on a 1.5 T MR system. the diffusion tensor pulse sequence used a SE-EPI with 6 diffusion gradie directions of (1, 1, 0), (-1, 1,0), (1, 0, 1), (-1, 0, 1), (0, 1, 1), (0, 1, -1) and also with no diffusion gradient. A b-factor of 500 sec/mm2 was used. Measurement parameter were as follows； TR/TE=10000 ms/99 ms, FOV=240 mm, matrix=128$\times$128, slice thickness/gap=6 mm/0 mm, bandwidth=91 kHz and the number of total slices=20. Four repeated axial diffusion images were averaged for diffusion tensor imaging. A total scan 11 of 4 min 30 sec was used. Six full diffusion tensor components of Dxx, Dyy, Dzz, Dxy, Dxz and Dyz were obtained using two-point linear regression model from 7 diffusion-weight images at each pixel and fractional anisotropy and lattice index images was estimated fr their eigenvectors and eigenvalues. Our program was written on a platform of IDL. W evaluated the qualities of fractional anisotropy and lattice index images of normal brains a knew whether our software for diffusion tensor imaging may be feasible.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.429-431
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• 2002

Metabolic analysis of biological tissues, the interventional radiology in MRT (Magnetic Resonance Treatment) and for clinical diagnoses, representation of 4-Dimensional (4D) structural information (x,y,z,t) of biological tissues is required. This paper discusses image representation techniques for those 4D MR Images. We have proposed an image reconstruction method for ultra-fast 3D MRI. It is based on image interpolation and prediction of un-acquired pictorial data in both of the real and the k-space (the acquisition domain in MRI). A 4D MR image is reconstructed from only two 3D MR images and acquired a few echo signals that are optimized by prediction of the tissue motion. This prediction can be done by the phase of acquired echo signal is proportioned to the tissue motion. On the other hand, reconstructed 4D MR images are represented as a 3D-movie by using computer graphics techniques. Rendered tissue surfaces and/or ROIs are displayed on a CRT monitor. It is represented in an arbitrary plane and/or rendered surface with their motion. As examples of the proposed representation techniques, the finger and the lung motion of healthy volunteers are demonstrated.

• Journal of Ginseng Research
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• v.36 no.4
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• pp.469-476
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• 2012

Raw ginseng root of Panax ginseng is graded according to its shape and the quality of its internal tissue. A variety of grades are sold with prices according to grade. If an inferior raw ginseng is purchased, the consumer experience an economic loss. This research was conducted in order to explore the possibility of developing a noninvasive method for investigating raw ginseng's internal tissue. It has been determined that computed tomography (CT) scanner images agreed with actual cross-sections of raw ginseng. CT images were obtained to assess the internal portions of raw ginseng, and CT scans of raw ginseng were thoroughly measured using the Hounsfield unit (HU) system, since it allows for a more detailed analysis compared to nuclear magnetic resonance imaging. HU is a measure of attenuation used for CT images, with each pixel being assigned a value using a scale on which air is defined as -1000, water as 0 and compact bone as +1000. It takes about one second to process are slice and produce an image of the raw ginseng by a one channel CT scanner. An image good enough to discriminate the internal tissues can be obtained in 1/24 seconds with a one-channel CT scanner. Using this method, images of raw ginseng can be obtained and the characteristics of the internal tissues can be observed in a short time.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.288-304
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• 2019

The growth of telemedicine-based wireless communication for images-magnetic resonance imaging (MRI) and computed tomography (CT)-leads to the necessity of learning the concept of image compression. Over the years, the transform based and spatial based compression techniques have attracted many types of researches and achieve better results at the cost of high computational complexity. In order to overcome this, the optimization techniques are considered with the existing image compression techniques. However, it fails to preserve the original content of the diagnostic information and cause artifacts at high compression ratio. In this paper, the concept of histogram based multilevel thresholding (HMT) using entropy is appended with the optimization algorithm to compress the medical images effectively. However, the method becomes time consuming during the measurement of the randomness from the image pixel group and not suitable for medical applications. Hence, an attempt has been made in this paper to develop an HMT based image compression by utilizing the opposition based improved harmony search algorithm (OIHSA) as an optimization technique along with the entropy. Further, the enhancement of the significant information present in the medical images are improved by the proper selection of entropy and the number of thresholds chosen to reconstruct the compressed image.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.83-86
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• 2019

Histogram equalization is extensively used for image contrast enhancement in various applications due to its effectiveness and its modest functions. In image research, image enhancement is one of the most significant and arduous technique. The image enhancement aim is to improve the visual appearance of an image. Different kinds of images such as satellite images, medical images, aerial images are affected from noise and poor contrast. So it is important to remove the noise and improve the contrast of the image. Therefore, for this purpose, we apply a median filter on MR image as the median filter remove the noise and preserve the edges effectively. After applying median filter on MR image we have used intensity transformation function on the filtered image to increase the contrast of the image. Than applied the histogram equalization (HE) technique on the filtered image. The simple histogram equalization technique over enhances the brightness of the image due to which the important information can be lost. Therefore, adaptive histogram equalization (AHE) and contrast limited histogram equalization (CLAHE) techniques are used to enhance the image without losing any information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2082-2102
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• 2024

Accurate segmentation of magnetic resonance (MR) images is crucial for providing doctors with effective quantitative information for diagnosis. However, the presence of weak boundaries, intensity inhomogeneity, and noise in the images poses challenges for segmentation models to achieve optimal results. While deep learning models can offer relatively accurate results, the scarcity of labeled medical imaging data increases the risk of overfitting. To tackle this issue, this paper proposes a novel fuzzy c-means (FCM) model that integrates a deep learning approach. To address the limited accuracy of traditional FCM models, which employ Euclidean distance as a distance measure, we introduce a measurement function based on the skewed normal distribution. This function enables us to capture more precise information about the distribution of the image. Additionally, we construct a regularization term based on the Kullback-Leibler (KL) divergence of high-confidence deep learning results. This regularization term helps enhance the final segmentation accuracy of the model. Moreover, we incorporate orthogonal basis functions to estimate the bias field and integrate it into the improved FCM method. This integration allows our method to simultaneously segment the image and estimate the bias field. The experimental results on both simulated and real brain MR images demonstrate the robustness of our method, highlighting its superiority over other advanced segmentation algorithms.

• Korean Journal of Radiology
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• v.2 no.4
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• pp.183-191
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• 2001

Objective: To document the signal characteristics of intracerebral hemorrhage (ICH) at evolving stages on diffusion-weighted images (DWI) by comparison with conventional MR images. Materials and Methods: In our retrospective study, 38 patients with ICH underwent a set of imaging sequences that included DWI, T1-and T2-weighted imaging, and fluid-attenuated inversion recovery (FLAIR). In 33 and 10 patients, respectively, conventional and echo-planar T2^* gradient-echo images were also obtained. According to the time interval between symptom onset and initial MRI, five stages were categorized: hyperacute (n=6); acute (n=7); early subacute (n=7); late subacute (n=10); and chronic (n=8). We investigated the signal intensity and apparent diffusion coefficient (ADC) of ICH and compared the signal intensities of hematomas at DWI and on conventional MR images. Results: DWI showed that hematomas were hyperintense at the hyperacute and late subacute stages, and hypointense at the acute, early subacute and chronic stages. Invariably, focal hypointensity was observed within a hyperacute hematoma. At the hyperacute, acute and early subacute stages, hyperintense rims that corresponded with edema surrounding the hematoma were present. The mean ADC ratio was 0.73 at the hyperacute stage, 0.72 at the acute stage, 0.70 at the early subacute stage, 0.72 at the late subacute stage, and 2.56 at the chronic stage. Conclusion: DWI showed that the signal intensity of an ICH may be related to both its ADC value and the magnetic susceptibility effect. In patients with acute stroke, an understanding of the characteristic features of ICH seen at DWI can be helpful in both the characterization of intracranial hemorrhagic lesions and the differentiation of hemorrhage from ischemia.

• Journal of the Korean Society of Radiology
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• v.2 no.2
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• pp.31-38
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• 2008

Line scan diffusion weighted imaging (LSDI) pulse sequence for 0.32 T magnetic resonance imaging (MRI) system was developed. In the LSDI pulse sequence, the imaging volume is formed by the intersection of the two perpendicular planes selected by the two slice-selective $\pi$/2-pulse and $\pi$-pulse and two diffusion sensitizing gradients placed on the both side of the refocusing $\pi$-pulse and the standard frequency encoding readout was followed. Since the maximum gradient amplitude for the MR system was 15 mT/m the maximum b value was $301.50s/mm^2$. Using the developed LSDI pulse sequence, the diffusion weighted images for the aqueous NaCl solution phantom and triacylglycerol solution phantom calculated from the line scan diffusion weighted images gives the same results within the standard error range (mean diffusivities = $963.90{\pm}79.83({\times}10^{-6}mm^2/s)$ at 0.32 T, $956.77{\pm}4.12({\times}10^{-6}mm^2/s)$ at 1.5 T) and the LSDI images were insensitive to the magnetic susceptibility difference and chemical shift.

• Investigative Magnetic Resonance Imaging
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• v.3 no.1
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• pp.47-52
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• 1999

Purpose : The purpose of this study was aimed to evaluate the BOLD(blood oxygen level dependent) contrast fMRI(functional MR imaging) in the occipital lobe and to compare with the metabolic changes based on H MRS (MR spectroscopy) and MRSI (MR spectroscopic imaging) before and after visual stimulation Materials and Methods : Healthy human volunteers (eight males and two females with 24-30 year age) participated in this study. All of the BOLD fMRI were acquired on a 1.5T MR with EPI during supervised visual stimulation in the occipital lobe. The red flicker with 8Hz was used for visual stimulation. After imaging acquisition, the MR images were transferred into unix workstation and processed with acquired from the same location based on the activation map. MRSI (magnetic resonance spectroscopic imaging) was also acquired to analyze the lactate changes before and after stimulation. Results : The activation maps were successfully produced by BOLD effect due to visual stimulation. NAA (N-acetyle aspartate)/Cr (creatine) ratio varied only from $1.79{\pm}0.28{\;}to{\;}1.88{\pm}0.20$ in activation area before and after stimulation. However, the signal intensity of lactate was elevated $9.48{\pm}4.38$ times higher than before activation. Lactate metabolite images were consistent with the activation maps. Conclusion : The BOLD contrast fMRI is enough sensitive to detect the activated area in human brain during the visual stimulation. Lactate metabolite map presents the evidence of lactate elevation on the same area of activation.

• Investigative Magnetic Resonance Imaging
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• v.13 no.1
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• pp.81-87
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• 2009

Purpose : We sought to evaluate enhancement of plaque with gadolinium-based contrast agent by magnetic resonance imaging (MRI) in comparison with histopathology, namely lipid-rich and macrophage-rich components that were two representative characteristics of plaque vulnerability using atherosclerotic rabbit aorta in order to determine which histopathologic component is relevant to the enhancement. Materials and Methods : New Zealand white rabbit (n=4, weight 3.0 to 3.5 kg, all male) was used for animal model of atherosclerosis. Atherosclerotic aortic lesions were induced by high-cholesterol diet and double balloon injury. T1-weight axial images were acquired before and after gadolinium-based contrast agent using a 3-T MRI. MR images and the matched histopathological sections (n=35) were divided into 4 quadrants or 3 (n=130). Enhancement ratio (ER, ER=SIpost/SIpre) on MRI was calculated for each quadrant and compared with histopathology in regard to lipid-rich and macrophage-rich areas. Results : Lipid-rich quadrants were 72 and fibrous quadrants were 58. The number of quadrants which had macrophage-rich areas was 105 and that of quadrants which did not have macrophage-rich areas was 25. ER was significantly higher in lipid-rich quadrants than in fibrous quadrants (mean ER 2.25c$\pm$0.41 vs. 2.72$\pm$0.65, p=0.013). ER poorly correlated with macrophage-rich areas when lipid-component was controlled (correlation coefficient -0.203, p=0.236). Conclusion : Lipid-rich plaques showed stronger enhancement than fibrous plaques using a standard gadolinium-based extracellular contrast agent. Macrophage infiltration did not correlate with degree of enhancement. Further study is warranted that account for optimal time of imaging after contrast injection using various plaque models from early to advanced stages and all possible parameters associated with contrast enhancement.