• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.218-228
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• 2021

Due to their high degree of freedom to transfer and acquire light, fiber optics can be used in the presence of strong magnetic fields. Hence, optical sensing and imaging based on fiber optics can be integrated with magnetic resonance imaging (MRI) diagnostic systems to acquire valuable information on biological tissues and organs based on a magnetic field. In this article, we explored the combination of MRI and optical sensing/imaging techniques by classifying them into the following topics: 1) functional near-infrared spectroscopy with functional MRI for brain studies and brain disease diagnoses, 2) integration of fiber-optic molecular imaging and optogenetic stimulation with MRI, and 3) optical therapeutic applications with an MRI guidance system. Through these investigations, we believe that a combination of MRI and optical sensing/imaging techniques can be employed as both research methods for multidisciplinary studies and clinical diagnostic/therapeutic devices.

• Clinics in Shoulder and Elbow
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• v.16 no.1
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• pp.10-16
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• 2013

Purpose: To know if magnetic resonance image (MRI) re-examination is needed before surgery, we compared the pre-operative MRI recorded at different time points and the corresponding arthroscopic findings. Materials and Methods: Depending on the timing of evaluation, the MRI was classified into three groups: group A, MRI was taken 1 month before the surgery (44 cases, average 16 days); group B, 1-6 months before the surgery (41 cases, average 91 days); and group C, 6-12 months before the surgery (25 cases, average 230 days). The anterior to posterior tear size (length) and medial retraction size (width) of rotator cuff tear were measured for each group and they were compared with the actual arthroscopic findings. Results: Results of this study showed that arthroscopic rotator cuff tear length and width were larger than those of MRI. The difference of the rotator cuff tear size was 3.6(${\pm}1.2$) mm of length and 0.6(${\pm}0.4$) mm of width in group A, 4.2(${\pm}1.7$) mm and 2.4(${\pm}1.1$) mm in group B, and 4.5(${\pm}2.1$) mm and 3.0(${\pm}1.5$) mm in group C. There was a tendency of the larger size difference for longer pre-operative period, but it was not statistically significant. Conclusion: The rotator cuff tear size did not show remarkable differences between pre-operative MRI taken within 1 year before surgery and the actual arthroscopy. It is concluded that additional MRI evaluation is not required within 1 year.

• Journal of radiological science and technology
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• v.39 no.3
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• pp.345-352
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• 2016

The purpose of this study was to needed basis of measure MRI CAD development for signal to noise ratio (SNR) by pulse sequence analysis from region of interest (ROI) in brain magnetic resonance imaging (MRI) contrast. We examined images of brain MRI contrast enhancement of 117 patients, from January 2005 to December 2015 in a University-affiliated hospital, Seoul, Korea. Diagnosed as one of two brain diseases such as meningioma and cysts SNR for each patient's image of brain MRI were calculated by using Image J. Differences of SNR among two brain diseases were tested by SPSS Statistics21 ANOVA test for there was statistical significance (p < 0.05). We have analysis socio-demographical variables, SNR according to sequence disease, 95% confidence according to SNR of sequence and difference in a mean of SNR. Meningioma results, with the quality of distributions in the order of T1CE, T2 and T1, FLAIR. Cysts results, with the quality of distributions in the order of T2 and T1, T1CE and FLAIR. SNR of MRI sequences of the brain would be useful to classify disease. Therefore, this study will contribute to evaluate brain diseases, and be a fundamental to enhancing the accuracy of CAD development.

• Journal of Yeungnam Medical Science
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• v.22 no.1
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• pp.43-51
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• 2005

Background: To examine the ultrasonographic and magnetic resonance (MRI) imaging findings of a cervical mass type cervical pregnancy. Materials and Methods: The ultrasonographic and MRI findings of 5 patients pathologically confirmed as having a cervical pregnancy were analyzed retrospectively. On ultrasonography, the size and echo pattern of the uterine cervix, the shape and echo pattern of the lesion, the degree and the pattern of blood flow on the color Doppler study and the spectral Doppler pattern were analyzed. The shape, signal intensity, and degree and pattern of enhancement of the lesion were evaluated on MRI. Results: The uterine cervix was enlarged and the size of the lesion was 6.1 to 7.1 (average, 6.5) cm. The endocervical canal was irregularly dilated and showed heterogeneous echogenicity in all 5 cases. Four of the 5 lesions were heterogeneously hyper- or mixed echoic and remaining one was relatively homogeneous echogenic. Doppler ultrasonography revealed an increased vascularity of the peritrophoblastic flow pattern. In all 4 cases where MRI performed, the lesion was irregular in shape and the margin was not sharply demarcated. The T2-weighed image showed that the lesions were mixed signal intensity. Three of the 4 lesions contained high signal intensity nodular portions and a low signal intensity rim was observed along the margin of the nodular portions. The T1-weighted image revealed multiple signal voids along the periphery of the lesions and high signal intensity portions as a result of hemorrhage were noted. The dynamic enhanced study showed that the high signal intensity portions on the T2-weighted image were strongly enhanced similar to the vessels on the early phase and the contrast enhancement gradually decreased with time. Conclusion: A cervical mass type cervical pregnancy can be correctly diagnosed using the patient's clinical symptom, the elevation in the serum ${\beta}$-HCG level, and characteristic ultrasonographic and MRI findings.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.132-137
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• 2019

The amount of data generated from medical images is increasingly exceeding the limits of professional visual analysis, and the need for automated medical image analysis is increasing. For this reason, this study evaluated the classification and accuracy according to the presence or absence of tumor using Inception V3 deep learning model, using MRI medical images showing normal and tumor findings. As a result, the accuracy of the deep learning model was 90% for the training data set and 86% for the validation data set. The loss rate was 0.56 for the training data set and 1.28 for the validation data set. In future studies, it is necessary to secure the data of publicly available medical images to improve the performance of the deep learning model and to ensure the reliability of the evaluation, and to implement modeling by improving the accuracy of labeling through labeling classification.

• Journal of Radiopharmaceuticals and Molecular Probes
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• v.1 no.2
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• pp.130-136
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• 2015

We evaluate the influence of MR contrast agent on positron emission tomography (PET) image using phantom, animal and human studies. Phantom consisted of 15 solutions with the mixture of various concentrations of Gd-based MR contrast agent and fixed activity of [$^{18}F$]FDG. Animal study was performed using rabbit and two kinds of MR contrast agents. After injecting contrast agent, CT or MRI scanning was performed at 1, 2, 5, 10, and 20 minutes. PET image was obtained using clinical PET/CT scan, and attenuation correction was performed using the all CT images. The values of HU, PET activity and MRI intensity were obtained from ROIs in each phantom and organ regions. In clinical study, patients (n=20) with breast cancer underwent sequential acquisitions of early [$^{18}F$]FDG PET/CT, MRI and delayed PET/CT. In phantom study, as the concentration increased, the CT attenuation and PET activity also increased. However, there was no relationship between the PET activity and the concentration in the clinical dose range of contrast agent. In animal study, change of PET activity was not significant at all time point of CT scan both MR contrast agents. There was no significant change of HU between early and delayed CT, except for kidney. Early and delayed SUV in tumor and liver showed significant increase and decrease, respectively (P<0.05). Under the condition of most clinical study (< 0.2 mM), MR contrast agent did not influence on PET image quantitation.

• Journal of radiological science and technology
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• v.41 no.6
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• pp.553-560
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• 2018

PET-CT and PET-MRI which integrates CT using ionized radiation and MRI using phenomena of magnetic resonance are determined to have the limitation to apply the semi-quantitative index, standardized uptake value (SUV), with the same level due to the fundamental differences of image capturing principle and reorganization, hence, their correlations were analyzed to provide their clinical information. To 30 study subjects maintaining pre-treatment, $^{18}F-FDG$ (5.18 MBq/㎏) was injected and they were scanned continuously without delaying time using $Biograph^{TM}$ mMR 3T (Siemens, Munich) and Biograph mCT 64 (Siemens, Germany), which is an integral type, under the optimized condition except the structural differences of both scanners. Upon the measurement results of $SUV_{max}$ setting volume region of interest with evenly distributed radioactive pharmaceuticals by captured images, $SUV_{max}$ mean values of PET-CT and PET-MRI were $2.94{\pm}0.55$ and $2.45{\pm}0.52$, respectively, and the value of PET-MRI was measured lower by $-20.85{\pm}7.26%$ than that of PET-CT. Also, there was a statistically significant difference in SUVs between two scanners (P<0.001), hence, SUV of PET-CT and PET-MRI cannot express the clinical meanings in the same level. Therefore, in case of the patients who undergo cross follow-up tests with PET-CT and PET-MRI, diagnostic information should be analyzed considering the conditions of SUV differences in both scanners.

• 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.

• Investigative Magnetic Resonance Imaging
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• v.17 no.2
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• pp.133-143
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• 2013

Purpose : To evaluate and compare the accuracy of magnetic resonance imaging (MRI) and ultrasound (US) for detection and estimation of invasion depth of colorectal carcinoma (CRC) by correlation with histopathologic findings in vitro, and to find out the best MR pulse sequence for accurate delineation of tumor from surrounding normal tissue. Materials and Methods: Resected specimens of CRC from 45 patients were examined about tumor detectability and invasion depth of US using high frequency (5-17 MHz) linear transducer in a tube filled with normal saline and MRI in a 8-channel quadrate head coil. The institutional review board approved this study and informed consent was waived. MRI with seven pulse sequences of in- and out-of-phases gradient echo T1 weighted images, fast spin echo T2 weighted image and its fat suppression image, fast imaging employing steady-state acquisition (FIESTA) and its fat suppression image, and diffusion weighted image (DWI) were performed. In each case, both imaging findings of MRI and US were evaluated independently for detection and estimation of invasion depth of tumor by consensus of two radiologists and were compared about diagnostic accuracy according to the histopathologic findings as reference standard. Seven MR pulse sequences were evaluated on the point of accurate delineation of tumor from surrounding normal tissue in each specimen. Results: In specimens of CRC, both imaging modalities of MRI (91.1%) and US (86.7%) showed relatively high diagnostic accuracy to detect tumor and evaluate invasion depth of tumor. In early CRC, diagnostic accuracy of US was 87.5% and that of MRI was 75.0%. There was no statistically significant difference between two imaging modalities (p > 0.05). The best pulse sequence among seven MR sequences for accurate delineation of tumor from surrounding normal tissue in each specimen of CRC was fast spin echo T2 weighted image. Conclusion: MRI and US show relatively high diagnostic accuracy to detect tumor and evaluate invasion depth of resected specimen of CRC. The most excellent pulse sequence of MRI for accurate delineation of tumor from surrounding normal tissue in CRC is fast spin echo T2 weighted image.

• Progress in Medical Physics
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• v.14 no.1
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• pp.34-42
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• 2003

In medical imaging, three-dimensional (3D) display using Virtual Reality Modeling Language (VRML) as a portable file format can give intuitive information more efficiently on the World Wide Web (WWW). The web-based 3D visualization of functional images combined with anatomical images has not studied much in systematic ways. The goal of this study was to achieve a simultaneous observation of 3D anatomic and functional models with planar images on the WWW, providing their locational information in 3D space with a measuring implement using VRML. MRI and ictal-interictal SPECT images were obtained from one epileptic patient. Subtraction ictal SPECT co-registered to MRI (SISCOM) was performed to improve identification of a seizure focus. SISCOM image volumes were held by thresholds above one standard deviation (1-SD) and two standard deviations (2-SD). SISCOM foci and boundaries of gray matter, white matter, and cerebrospinal fluid (CSF) in the MRI volume were segmented and rendered to VRML polygonal surfaces by marching cube algorithm. Line profiles of x and y-axis that represent real lengths on an image were acquired and their maximum lengths were the same as 211.67 mm. The real size vs. the rendered VRML surface size was approximately the ratio of 1 to 605.9. A VRML measuring tool was made and merged with previous VRML surfaces. User interface tools were embedded with Java Script routines to display MRI planar images as cross sections of 3D surface models and to set transparencies of 3D surface models. When transparencies of 3D surface models were properly controlled, a fused display of the brain geometry with 3D distributions of focal activated regions provided intuitively spatial correlations among three 3D surface models. The epileptic seizure focus was in the right temporal lobe of the brain. The real position of the seizure focus could be verified by the VRML measuring tool and the anatomy corresponding to the seizure focus could be confirmed by MRI planar images crossing 3D surface models. The VRML application developed in this study may have several advantages. Firstly, 3D fused display and control of anatomic and functional image were achieved on the m. Secondly, the vector analysis of a 3D surface model was defined by the VRML measuring tool based on the real size. Finally, the anatomy corresponding to the seizure focus was intuitively detected by correlations with MRI images. Our web based visualization of 3-D fusion image and its localization will be a help to online research and education in diagnostic radiology, therapeutic radiology, and surgery applications.