• Journal of Biomedical Engineering Research
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• v.21 no.2
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• pp.145-156
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• 2000

본 논문에서는 중앙시상 두뇌 자기공명영상 분할결과를 이용한 3차원 시상 두뇌 자기공명영상의 자동분할기법을 제안한다. 제안된 알고리즘에서는 먼저 3차원 시상 두뇌 자기공명영상의 중앙영상을 분할하고, 분할된 중앙두뇌 자기공명영상을 인접하는 영상에 마스크로 적용한다. 이 때 마스크 적용으로 인하여 인접하는 영상이 절단되는 문제가 발생할 수 있다. 이러한 문제를 해결하기 위하여 절단 영역의 경계점을 검출한 후, 절단 영역에 대한 경로 재설정을 통해 절단 영역을 복원한다. 이러한 경로 재설정을 위해 connectivity-based threshold segmentation algorithm을 사용하였다. 실험결과 제안된 알고리즘의 유용성을 확인할 수 있었다.

• Journal of Korean Neurosurgical Society
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• v.47 no.1
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• pp.68-70
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• 2010

We report a case of intracranial dissemination developing approximately 4 months after partial removal of a spinal cord anplastic astrocytoma in a 22-year-old male. He presented with paraplegia on initial admission at a local hospital. Spinal magnetic resonance (MR) images disclosed multiple intramedullary lesions at the T3-11. The tumor was partially removed. The final histologic diagnosis was anaplastic astrocytoma. Four months after the operation, he was admitted with the symptoms of headache and deterioration of consciousness. MR images showed enhanced lesions in the anterior horn of the left lateral ventricle, and septum pellucidum. He underwent computed tomography-guided stereotactic biopsy and histological appearance was consistent with anaplastic astrocytoma. The clinical course indicates that the tumor originated in the spinal cord and extended into the subarachnoid space, first the spinal canal and later intracranial.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.4
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• pp.203-207
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• 2013

The appropriate handling of motion artifacts is essential for clinical diagnosis in magnetic resonance imaging (MRI). In many cases, motion is an inherent part of MR images because it is difficult to control during MR imaging. As the motion in the human body occur in a deformable manner, they are difficult to deal with. This paper proposes a novel detection method for periodically moving regions to produce MR images with less motion artifacts. When the data is acquired by the radial trajectory, the proposed method can extract the deformable region easily using the difference in the modulated sinograms, which have different periodic phase terms. The simulation results applied to the various cases confirmed the good performance of the proposed method.

• Proceedings of the KSMRM Conference
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• 2002.11a
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• pp.135-135
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• 2002

Purpose： To assess diagnostic accuracy of dynamic contrast enhanced MR mammography in differentiating between benign and malignant lesions. Materials and methods： Ninety-three patients with suspicious mammographic, sonographic or palpable findings underwent pre- or postoperative contrast-enhanced MR imaging of breast using three dimensional fast low-angle shot (3D FLASH) sequence (16/4 msec［repetition time / echo time］, 20 flip angle, 3mm slice thickness with no slice gap, 256 by 256 in-plane matrix) covering whole breasts. T1 weighted images were obtained before and after bolus administration of gadopentetate dimeglumine (0.15 mmol/kg). Subtraction images and time-signal intensity curves of region of interest were obtained sequentially and correlated with pathologic diagnoses of lesions.

• Journal of Korean Neurosurgical Society
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• v.45 no.6
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• pp.375-377
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• 2009

A 49-year-old woman presented with headache, vomiting and visual disturbance. Neurological examination revealed bitemporal hemianopsia with poor visual acuity. Magnetic resonance imaging showed a bulky intra-suprasellar mass, which was isointense with brain parenchyma on T1-weighted images, and slightly hyperintense on T2-weighted images. After gadolinium administration, the mass was homogeneously enhanced. The mass was partially removed by the endonasal transsphenoidal approach and then the remnant mass was totally removed by the transcranial approach five months later. We found a yellowish mass which was attached to the diaphragm sellae in operation field. Histopathological examination of the tumor revealed the characteristic features of a schwannoma. We report an unusual case of an intra-suprasellar schwannoma resembling a non-functioning pituitary macroadenoma both clinically and radiologically.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3479-3492
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• 2022

Longitudinal quantification of brain changes due to development, aging or disease plays an important role in the filed of personalized-medicine applications. However, due to the temporal variability in shape and different imaging equipment and parameters, estimating anatomical changes in longitudinal studies is significantly challenging. In this paper, a longitudinal Magnetic Resonance(MR) brain image segmentation algorithm proposed by combining intensity information and anisotropic smoothness term which contain a spatial smoothness constraint and longitudinal consistent constraint into a variational framework. The minimization of the proposed energy functional is strictly and effectively derived from a fast optimization algorithm. A large number of experimental results show that the proposed method can guarantee segmentation accuracy and longitudinal consistency in both simulated and real longitudinal MR brain images for analysis of anatomical changes over time.

• Smart Media Journal
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• v.12 no.7
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• pp.52-58
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• 2023

Alzheimer's disease is one type of dementia, the symptoms can be treated by detecting the disease at its early stages. Recently, many computer-aided diagnosis using magnetic resonance image(MRI) have shown a good results in the classification of AD. Taken these MRI images and feed to Free surfer software to extra the features. In consideration, using T1-weighted images and classifying using the convolution neural network (CNN) model are proposed. In this paper, taking the subjects from ADNI of subcortical and cortical features of 190 subjects. Consider the study to reduce the complexity of the model by using the single layer in the Res-Net, VGG, and Alex Net. Multi-class classification is used to classify four different stages, CN, EMCI, LMCI, AD. The following experiment shows for respective classification Res-Net, VGG, and Alex Net with the best accuracy with VGG at 96%, Res-Net, GoogLeNet and Alex Net at 91%, 93% and 89% respectively.

• Progress in Medical Physics
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• v.2 no.1
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• pp.3-16
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• 1991

Abstract. An area of particularly rapid technological growth in the last 15 years has been medical imaging (conventional X-ray, ultrasound, X-ray computed tomography (CT), magnetic resonance imaging (MRI). As the number and complexity of imaging studies rises, it becomes ever more important to distribute these images and the associated diagnoses in a timely and cost-effective fashion. The purpose of this paper is to describe the requirements for a future digital radiology system which will efficiently handle the large volume of images that generated, add new functionality to improve productivity of physicians, technologists, and other health care providers, and provide enough flexibility to allow the system to grow as medical image technology grows.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.209-213
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• 2023

In recent years, the image processing mechanisms are used widely in several medical areas for improving earlier detection and treatment stages, in which the time factor is very important to discover the disease in the patient as possible as fast, especially in various cancer tumors such as the liver cancer. Liver cancer has been attracting the attention of medical and sciatic communities in the latest years because of its high prevalence allied with the difficult treatment. Statistics indicate that liver cancer, throughout world, is the one that attacks the greatest number of people. Over the time, study of MR images related to cancer detection in the liver or abdominal area has been difficult. Early detection of liver cancer is very important for successful treatment. There are few methods available to detect cancerous cells. In this paper, an automatic approach that integrates the intensity-based segmentation and k-means clustering approach for detection of cancer region in MRI scan images of liver.

• Investigative Magnetic Resonance Imaging
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• v.19 no.3
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• pp.162-167
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• 2015

Purpose: To evaluate the usefulness of quantitative analysis of the facial nerve using contrast-enhanced three-dimensional (CE 3D) fluid-attenuated inversion recovery-volume isotopic turbo spin echo acquisition (FLAIR-VISTA) for the diagnosis of Bell's palsy in pediatric patients. Materials and Methods: Twelve patients (24 nerves) with unilateral acute facial nerve palsy underwent MRI from March 2014 through March 2015. The unaffected sides were included as a control group. First, for quantitative analysis, the signal intensity (SI) and relative SI (RSI) for canalicular, labyrinthine, geniculate ganglion, tympanic, and mastoid segments of the facial nerve on CE 3D FLAIR images were measured using regions of interest (ROI). Second, CE 3D FLAIR and CE T1-SE images were analyzed to compare their diagnostic performance by visual assessment (VA). The sensitivity, specificity, and accuracy of RSI measurement and VA were compared. Results: The absolute SI of canalicular and mastoid segments and the sum of the five mean SI (total SI) were higher in the palsy group than in the control group, but with no significant differences. The RSI of the canalicular segment and the total SI were significantly correlated with the symptomatic side (P = 0.028 and 0.015). In 11/12 (91.6%) patients, the RSI of total SI resulted in accurate detection of the affected side. The sensitivity, specificity, and accuracy for detecting Bell's palsy were higher with RSI measurement than with VA of CE 3D FLAIR images, while those with VA of CE T1-SE images were higher than those with VA of CE 3D FLAIR images. Conclusion: Quantitative analysis of the facial nerve using CE 3D FLAIR imaging can be useful for increasing the diagnostic performance in children with Bell's palsy when difficult to diagnose using VA alone. With regard to VA, the diagnostic performance of CE T1-SE imaging is superior to that of CE 3D FLAIR imaging in children. Further studies including larger populations are necessary.