• Korean Journal of Digital Imaging in Medicine
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• v.17 no.1
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• pp.43-48
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• 2015

Intracrnial 3D TOF MR angiography was performed in 30 normal volunteers with both 1.5 and 3.0 T MRI system with high resolutions. Used Voxel sizes were $0.39{\times}0.39{\times}0.2$(1.5 T) and $0.19{\times}0.19{\times}0.35$(3.0 T), respectively. High image quality and depiction of small vessel branches were equality demonstrated with 1.5 T and 3.0 T HR TOF MRA(p<0.05). Intracranial high resolution TOF MRA with 1.5 T and 3.0 T provides high diagnostic information with having merits and demerits in depiction of vascular branches.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.1-6
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• 2007

Two impedance imaging systems of multi-frequency electrical impedance tomography (MFEIT) and magnetic resonance electrical impedance tomography (MREIT) are described. MFEIT utilizes boundary measurements of current-voltage data at multiple frequencies to reconstruct cross-sectional images of a complex conductivity distribution (${\sigma}+i{\omega}{\varepsilon}$) inside the human body. The inverse problem in MFEIT is ill-posed due to the nonlinearity and low sensitivity between the boundary measurement and the complex conductivity. In MFEIT, we therefore focus on time- and frequency-difference imaging with a low spatial resolution and high temporal resolution. Multi-frequency time- and frequency-difference images in the frequency range of 10 Hz to 500 kHz are presented. In MREIT, we use an MRI scanner to measure an internal distribution of induced magnetic flux density subject to an injection current. This internal information enables us to reconstruct cross-sectional images of an internal conductivity distribution with a high spatial resolution. Conductivity image of a postmortem canine brain is presented and it shows a clear contrast between gray and white matters. Clinical applications for imaging the brain, breast, thorax, abdomen, and others are briefly discussed.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.45-48
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• 1995

Visualization of three dimensional medical images has been studied in many ways. For CT and MRI data, 3D rendering schemes are commercially available and widly used. However visualization of ultrasonic 3D data is not popular yet, even though its potentional in medical diagnosis seems very high. In this paper we try to visualize 3D ultrasonic data. The basic method is adopted from the volume rendering technique. Based on the characteristics of the ultrasonic images, 3D visualization algorithm is developed and applied for the 3D image set of a dog heart.

• ETRI Journal
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• v.31 no.2
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• pp.237-239
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• 2009

A whole-body voxel model of a 7-year-old male volunteer was developed from 384 axial magnetic resonance images (MRIs). The MRIs were acquired with intervals of 3 mm for the entire body in a body coil. In order to reduce the MRI acquisition time for the child, the repetition and echo times under T1 weighted image were chosen to be 566 ms and 8 ms, respectively. The MRIs were classified according to 30 types of tissues with known electrical parameters. The developed voxel model was adjusted to the physical average of 7-year-old Korean boys. The body weight of the adjusted model, calculated with the mass tissue densities, is within a 6% difference from the 50th percentile weight.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.1
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• pp.131-138
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• 2000

This paper works on development of an algorithm for mapping of cerebral perfusion parameters using the gamma-variate curve fitting. The signal intensity variate curve according to time measured in each pixel of perfusion MRI is nonlinear, and various hemodynamic parameters are not computed accurately. Levenberg-Marquardt algorithm(LMA), nonlinear optimum algorithm with high convergent speed and stability, is used to compute them. That is, the signal intensity variate curve is fitted by the gamma-variate function. Various hemodynamic parameters - Cerebral Blood Volume(C.B.V), Mean Transit Time(M.T.T), Cerebral Blood Flow(C.B.F), Time-to-Peak(T.T.P), Bolus Arrival Time(B.A.T), Maximum Slope(M.S) - are computed using LMA.

• Journal of Korean Neurosurgical Society
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• v.39 no.4
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• pp.310-313
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• 2006

Although lipomyelomeningocele and dermoid cyst are formed during a similar embryologic developmental stage of 'neural tube formation', they are caused by entirely different embryologic mechanisms. We encountered a case, which has not been previously reported, that had a lumbar subcutaneous dermoid cyst associated with lipomyelomeningocele. A 52-year-old man presented with a slowly growing lumbar mass of 3 years duration, which had been present since birth. Lumbosacral magnetic resonance imaging[MRI] showed lipomyelomeningocele at the L3, 4 and 5 levels and a subcutaneous cystic mass of high signal intensity on the T2 weighted image and iso or low signal intensity on the T1 weighted image. He underwent total resection of the lumbar subcutaneous mass. Intraoperative findings and histological examination were consistent with the preoperative diagnosis of a 'dermoid cyst'. We demonstrate that the formation of a dermoid cyst might coexist with lipomyelomeningocele during the embryologic developmental stage.

• Investigative Magnetic Resonance Imaging
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• v.23 no.1
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• pp.70-74
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• 2019

Cerebral air embolism (CAE) is a rare complication of various medical procedures. It manifests with symptoms similar to those of typical acute cerebral infarction, however the treatment is quite different. We present a case of arterial CAE that was associated with a disconnected central venous catheter and appeared as punctate dark signal intensities with aliasing artifacts on the susceptibility-weighted filtered phase magnetic resonance image. The susceptibility-weighted filtered phase image can be helpful for diagnosing CAE and the magnetic resonance imaging reflects the pathophysiology of CAE.

• 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.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.5-6
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• 2020

현대 의학에서 의료 영상은 수많은 영상처리 의료기기의 핵심이다. PACS(Picture Archiving Communication System)를 통해 관리되는 의료 영상 자료들은 요청에 따라 저장, 검색 및 전송을 수행하여 신속한 의료 서비스를 가능하게 한다. 그러나 만약에 관리자의 실수로 의료 영상 데이터가 바뀐다면 이는 사용자로 하여금 불편함과 낮은 신뢰성을 야기한다. 그리하여 본 논문에서는 서포트 벡터 머신 기반의 HOG(Histogram of Oriented Gradients) 특징 벡터를 이용하여 X-ray와 MRI(Magnetic Resonance Imaging) 사진을 분류하고 의료 영상 분류의 가능성을 제시하는 것을 목표로 한다.

• 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.