• Neurospine
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• v.15 no.4
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• pp.383-387
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• 2018

Objective: Lower back pain (LBP) is a worldwide health problem, and magnetic resonance imaging (MRI) is a common modality used to aid in its diagnosis. Although specific guidelines for assessing the necessity of MRI usage exist, the use of MRI as the initial imaging method for LBP seems to be more common than necessary in general practice. Methods: We conducted a retrospective chart review of 313 patients who had undergone MRI of the lumbosacral spine during 2014-2015. We recorded and compared various factors, including age, sex, body mass index, current smoking status, race, symptoms, MRI findings, and progression to surgery within the next year. All rates were compared according to whether the MRI results showed radiographically significant findings (MRI-positive) or not (MRI-negative) using the chi-square or Fisher exact tests (if the expected cell count was <5). All analyses were performed using SAS version 9.4. Results: There were no statistically significant differences in the rates of each symptom between the MRI-positive and MRI-negative groups, which accounted for 58.5% (183 of 313) and 41.5% (130 of 313) of the MRIs, respectively. The difference in the rate of surgery in the next year (18% among MRI-positive patients and 8.5% among MRI-negative patients) was found to be statistically significant (p<0.05). Conclusion: Based on our findings, 41.5% of patients underwent lumbar MRI unnecessarily and 81% of patients with positive MRIs did not have surgery within the next year. Further physician training is needed to avoid unnecessary investigations and expenditures.

• Annals of Clinical Neurophysiology
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• v.14 no.1
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• pp.36-40
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• 2012

Nephrogenic systemic fibrosis (NSF) is a systemic disease that affects the skin and other tissues in patients with renal insufficiency and exposure to gadolinium-containing contrast. A 55-year-old woman with end-stage renal disease on hemodialysis was consulted for progressive general weakness. After she had undergone multiple MRIs with gadolinium-containing contrast media, muscle weakness and skin lesions were developed. Her skin and muscle biopsy specimens showed CD34+ fibroblast entrapping collagen bundles. There are few reports of NSF with myopathy.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.04a
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• pp.328-331
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• 2000

In this paper , we propose a texture feature extraction method of reduce the massive computational time on extracting texture, features of large sized medical such as MRI, CT-scan , and an index structure, called GLTFT, to speed up the retrieval performance. For these, the original image is transformed into a compressed image by Wavelet transform , and textural features such as contrast, energy, entropy, and homogeneity of the compressed image is extracted by using GLCM(Gray Level Co-occurrence Metrix) . The proposed index structure is organized by using the textural features. The processing in compressed domain can give the solution of storage space and the reduction of computational time of feature extracting . And , by GLTFT index structure, image retrieval performance can be expected to be improved by reducing the retrieval range . Our experiment on 270 MRIs as image database shows that shows that such expectation can be got.

• Investigative Magnetic Resonance Imaging
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• v.20 no.3
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• pp.141-151
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• 2016

Purpose: Advances of magnetic resonance imaging (MRI), especially that of the Ultra-High Field (UHF) MRI will be reviewed. Materials and Methods: Diffusion MRI data was obtained from a healthy adult young male of age 30 using a 7.0T research MRI scanner (Magnetom, Siemens) with 40 mT/m maximum gradient field. The specific imaging parameters used for the data acquisition were a single shot DW echo planar imaging. Results: Three areas of the imaging experiments are focused on for the study, namely the anatomy, angiography, and tractography. Conclusion: It is envisioned that, in near future, there will be more 7.0T MRIs for brain research and explosive clinical application research will also be developed, for example in the area of connectomics in neuroscience and clinical neurology and neurosurgery.

• Journal of Yeungnam Medical Science
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• v.27 no.1
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• pp.37-41
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• 2010

Hypoglycemic encephalopathy is a rare problem among diabetic patients who are receiving treatment with insulin or other glucose-lowering drugs. The MRIs of patients with hypoglycemic encephalopathy commonly show scattered lesions in the cerebral cortex, hippocampus and basal ganglia, but lesions in the cerebellum or brain stem are extremely rare. A 44-year-old alcoholic woman without diabetes was admitted with a semicomatose mentality and seizure with severe hypoglycemic encephalopathy with extensive brain lesions seen on MRI at the middle cerebellar peduncle and midbrain, as well as in the other brain areas.

• Brain Tumor Research and Treatment
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• v.6 no.2
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• pp.101-104
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• 2018

Pheochromocytoma (PCC) is a neuroendocrine tumor that mainly arises from the medulla of the adrenal gland. Some PCCs become malignant and metastasize to other organs. For example, it typically involves skeletal system, liver, lung, and regional lymph nodes. However, only a few cases of PCC with brain metastasis have been reported worldwide. We report a case of metastatic brain tumor from PCC in South Korea in 2016. A 52-year-old man presented with headache, dizziness and motor aphasia. He had a medical history of PCC with multi-organ metastasis, previously underwent several operations, and was treated with chemotherapy and radiotherapy. Brain MRIs showed a brain tumor on the left parietal lobe. Postoperative pathology confirmed that the metastatic brain tumor derived from malignant PCC. This is the first report PCC with brain metastasis in South Korea.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.343-351
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• 2022

A brain tumor forms when some tissue becomes old or damaged but does not die when it must, preventing new tissue from being born. Manually finding such masses in the brain by analyzing MRI images is challenging and time-consuming for experts. In this study, our main objective is to detect the brain's tumorous part, allowing rapid diagnosis to treat the primary disease instantly. With image processing techniques and deep learning prediction algorithms, our research makes a system capable of finding a tumor in MRI images of a brain automatically and accurately. Our tumor segmentation adopts the U-Net deep learning segmentation on the standard MICCAI BRATS 2018 dataset, which has MRI images with different modalities. The proposed approach was evaluated and achieved Dice Coefficients of 0.9795, 0.9855, 0.9793, and 0.9950 across several test datasets. These results show that the proposed system achieves excellent segmentation of tumors in MRIs using deep learning techniques such as the U-Net algorithm.

• Korean Journal of Veterinary Research
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• v.63 no.3
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• pp.26.1-26.5
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• 2023

Syringobulbia is a rare neurological disorder characterized by a fluid-filled cavity in the brainstem. In this study, clinical signs, features on magnetic resonance imaging (MRI), and the diseases present concurrently with syringobulbia were investigated in 33 small breed dogs. Most dogs (97%) had concurrent syringomyelia, and some dogs (24%) presented with vestibular or cranial nerve symptoms associated with the medulla oblongata. MRIs revealed slit-like, bulbous, and vertical linear shapes of the cavities on T2-weighted hyperintense and T1-weighted hypointense signals similar to the cerebrospinal fluid. Chiari-like malformations were identified in all dogs. This study highlights the association of syringobulbia with syringomyelia and Chiari-like malformations in small breed dogs with or without brainstem-associated clinical signs.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.33 no.4
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• pp.367-374
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• 2007

Purpose: The diagnostic relevancies and characteristics and of clinical methods in the diagnosis of internal derangement(ID) were tested by comparing the results of them with those of magnetic resonance imaging(MRI). Methods: 75 patients(150 temporomandibular joints; TMJs), who were suspected to have ID by clinical diagnoses, were included. Clinical diagnoses including mouth opening pathway and TMJ sound were conducted and MRI takings were done. Accuracies, sensitivities, specificities, positive predictive values, and negative predictive values of clinical diagnosis, mouth opening pathway, and TMJ sound were calculated by comparing with diagnoses with MRIs. Results: Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of clinical diagnosis were 59.3%, 83%, 49%, 81%, and 51%. They were 59%, 82%, 25%, 73%, and 35% for mouth opening pathways. Although deviation was somewhat accurate for representing disc displacement with reduction(ADDWR), other discrepancies on opening pathways were not clinically relevant. Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of clicking sounds were 85%, 49%, 78%, 85%, and 37%. TMJs with crepitus were only three. But all TMJs with crepitus were diagnosed to have disc displacement without reduction(ADDWOR). Conclusion: When compared with diagnoses with MRIs, clinical diagnoses for ID were not so accurate. But they were suitable for screening tests for ID. Opening pathways and TMJ sounds were not so relevant in the diagnoses of IDs and so it was concluded that considerations for other factors must be included in the diagnoses of IDs.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.65-72
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• 2010

Nowadays, most hospitals have been used to create MRI or CT and managed them. Doctors depend on fast access to images such as magnetic resonance imaging (MRIs), computerized tomography (CT) scans, and X-rays for accurate diagnoses. Those image data are related privacy of a patient. Therefore, it should be protected from hackers and managed perfectly. In this paper, we propose a data hiding method into MRI or CT related a condition and intervention of a patient, and it is suggested that how to authenticate patient information from an image. In this way, we create hash code using HMAC with patient information, and hash code and patient information is hided into an image. After then, doctor will check authentication using HMAC. In addition, we use a reversible data hiding DE(Difference Expansion) algorithm to hide patient information. This technique is possible to reconstruct the original image with stego image. Therefore, doctor can easily be possible to check condition of a patient. As a consequence of an experiment with MRI image, data hiding, extraction and reconstruct is shown compact performance.