Medical Imaging


The usage of MRI(Magnetic Resonance Image) systems has been increasing gradually in medical imaging services because they can characterize and discriminate properties. MRI systems produce high resolution and high contrast images and have no radiation exposures which are different from CT(Computed Tomography). This research is for diagnosing osteoarthritis through medical imaging methods which have advantages in analyzing the morphological and biochemical measurement of arthrosis. With our medical professional associates, we will devote effort to developing an efficient, accurate and customized application software and making it commercial.

MEMVA (Multi Echo MRI Visualization and analysis) for automatic Cartilage detection

Medical imaging researches performed in our laboratory can be divided into 4 categories:

Noise removal

A lot of research works have been made for removing the noise in the knee MR image acquisition stage. However, the real MR images still possess certain types of noise such as Gaussian noise from devices and flow-artifact noise due to strong blood stream in the artery near the joint region. The blood flow occasionally produces intravascular high signal intensities due to flow related enhancement, even echo rephrasing an diastolic pseudogating. The pulsatile laminar flow within vessels often produces a complex multilayered band that usually propagates outside the vessel in the phase encoded direction. Blood flow artifacts should be considered as a special subgroup of motion artifacts.

Related papers :

Xuenan Cui, Hakil Kim, Seongwook Hong, and Kyu-sung Kwack “A novel noise removal using homomorphic normalization for multi-echo knee MRI” IEICE Electronics Express, Vol.8, No.8, 604-611

Seongwook Hong, Xuenan Cui, Shengzhe Li, Naw Chit Too June, Hakil Kim, and Kyu-sung Kwack “Enhanced Edge Detection based on Canny operator MR images” 2010 IPIU. Jeju. 2010 01.27~01.29

Seongwook Hong, Xuenan Cui, Hakil Kim, and Kyu-sung Kwack “Noise removal for Multi-echo MR images using Global Enhancement” 2010 SMC. Turkey. 2010 10.10~10.13.

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Cartilage segmentation

Knee Osteoarthritis (OA) is a prevalent disease characterized by cartilage degradation. Therefore, the cartilage is most important information for early diagnosis of OA. Recently, semi-automatic and fully automatic cartilage segmentation methods have been studied by worldwide researchers.

Related papers :

X. Cui, S. Li, M. Yu, M. Ma, H. Kim, K.S. Kwack and B.H. Min “Automatic Cartilage Segmentation using Multi-level Gaussian Filters” 2012 UKC, Los Angeles, 2012 08.08~08.11.

Xuenan Cui, Seongwook Hong, Shengzhe Li, Naw Chit Too June, Hakil Kim, and Kyu-sung Kwack “Knee MR image segmentation for early OA diagnosis using multi-echo imagery” 2010 IPIU. Jeju. 2010 01.27~01.29

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3D Image Registration

Image Registration is the process of finding the geometric transformation of two images of the same scene which are taken at different time, from different sensor or from different viewpoint and aligns them into the same spatial coordinate. In medical imaging, image registration has been one of the important research areas and the development of the effective registration technique has been demanding for the purpose of efficient clinical applications.

Related papers :

Naw Chit Too June, Xuenan Cui, Shengzhe Li, Kyu-sung Kwack, Hakil Kim “Parallel processing of 3D medical image registration by OpenCL”2012 IPIU. Jeju. 2012.02.15~02.17

Naw Chit Too June, Xuenan Cui, Seongwook Hong, Shengzhe Li, Enhua Li, Hakil Kim, Kyu-sung Kwack “FAIR: Fast and Accurate Image Registration method for 3D CT Registration”2011 IPIU. Jeju. 2011.02.16~02.18

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3D Visualization

Using 3D visualization to present information of keen MRI is convenient for doctors to diagnosing osteoarthritis. Volume rendering technique, polygonal rendering technique and so on are used for 3D visualization.

Related papers:

이성철 최학남 홍성욱 너치투준 김학일 “VTK를 이용한 무릎 MRI의 3차원 가시화” 2010한국컴퓨터종합학술대회 논문집Vol.37,No.1(B)

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Useful links:

SPIE Medical Imaging™
MICCAI Conferences