• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.455-458
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• 2010

Extracting the brain from magnetic resonance imaging head scans is an essential preprocessing step of which the accuracy greatly affects subsequent image analysis. The currently popular Brain Extraction Tool produces a brain mask which may be too smooth for practical use to reduce the accuracy. This paper presents a novel and indirect brain extraction method based on non-brain tissue segmentation. Based on ITK, the proposed method allows a non-brain contour by using region growing to match with the original image naturally and extract the brain tissue. Experiments on two set of MRI data and 2D brain image in horizontal plane and 3D brain model indicate successful extraction of brain tissue from a head.

• Investigative Magnetic Resonance Imaging
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• v.12 no.2
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• pp.131-141
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• 2008

Purpose : To investigate the feasibility and accuracy of Proton Resonance Frequency (PRF) shift based magnetic resonance (MR) temperature mapping utilizing the self-developed center array-sequencing phase unwrapping (PU) method for non-invasive temperature monitoring. Materials and Methods : The computer simulation was done on the PU algorithm for performance evaluation before further application to MR thermometry. The MR experiments were conducted in two approaches namely PU experiment, and temperature mapping experiment based on the PU technique with all the image postprocessing implemented in MATLAB. A 1.5T MR scanner employing a knee coil with $T2^*$ GRE (Gradient Recalled Echo) pulse sequence were used throughout the experiments. Various subjects such as water phantom, orange, and agarose gel phantom were used for the assessment of the self-developed PU algorithm. The MR temperature mapping experiment was initially attempted on the agarose gel phantom only with the application of a custom-made thermoregulating water pump as the heating source. Heat was generated to the phantom via hot water circulation whilst temperature variation was observed with T-type thermocouple. The PU program was implemented on the reconstructed wrapped phase images prior to map the temperature distribution of subjects. As the temperature change is directly proportional to the phase difference map, the absolute temperature could be estimated from the summation of the computed temperature difference with the measured ambient temperature of subjects. Results : The PU technique successfully recovered and removed the phase wrapping artifacts on MR phase images with various subjects by producing a smooth and continuous phase map thus producing a more reliable temperature map. Conclusion : This work presented a rapid, and robust self-developed center array-sequencing PU algorithm feasible for the application of MR temperature mapping according to the PRF phase shift property.

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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• pp.60-67
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• 2020

Recently, artificial intelligence related technologies including machine learning are being applied to various fields, and the demand is also increasing. In particular, with the development of AR, VR, and MR technologies related to image processing, the utilization of computer vision based on deep learning has increased. The algorithms for object recognition and detection based on deep learning required for image processing are diversified and advanced. Accordingly, problems that were difficult to solve with the existing methodology were solved more simply and easily by using deep learning. This paper introduces various deep learning-based object recognition and extraction algorithms used to detect and recognize various objects in an image and analyzes the technologies that attract attention.

• Investigative Magnetic Resonance Imaging
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• v.14 no.1
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• pp.10-20
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• 2010

Purpose : Recently, the Recon Challenge at the 2009 ISMRM workshop on Data Sampling and Image Reconstruction at Sedona, Arizona was held to evaluate feasibility of highly accelerated acquisition of time resolved contrast enhanced MR angiography. This paper provides the step-by-step description of the winning results of k-t FOCUSS in this competition. Materials and Methods : In previous works, we proved that k-t FOCUSS algorithm successfully solves the compressed sensing problem even for less sparse cardiac cine applications. Therefore, using k-t FOCUSS, very accurate time resolved contrast enhanced MR angiography can be reconstructed. Accelerated radial trajectory data were synthetized from X-ray cerebral angiography images and provided by the organizing committee, and radiologists double blindly evaluated each reconstruction result with respect to the ground-truth data. Results : The reconstructed results at various acceleration factors demonstrate that each components of compressed sensing, such as sparsifying transform and incoherent sampling patterns, etc can have profound effects on the final reconstruction results. Conclusion : From reconstructed results, we see that the compressed sensing dynamic MR imaging algorithm, k-t FOCUSS enables high resolution time resolved contrast enhanced MR angiography.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.8
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• pp.73-82
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• 2004

In this paper, implementation of obstacle avoidance of a nonholonomic mobile robot in unstructured environment is introduced. To avoid obstacles, first, a reference collision-free path for the MR is generated off-line using HJB-based optimal path planning method. A controller is designed using integrator backstepping method for tracking the generated reference path. To implement the designed controller, a control system are needed and composed of camera system and PIC-based controller. The workspace is observed by a ceiling-mounted USB camera as part of an un-calibrated camera system. Thus the positional information of the MR is updated frequently and the MR can get the useful inputs for its tracking controller. The whole control system is realized by integrating a computer with PIC-based microprocessor using wireless communication: the image processing control module and path planning module serve as high level computer control while the device control serves as low level PIC microprocessor control. The simulation and experimental results show the effectiveness of the designed control system.

• 전자공학회논문지 IE
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• v.43 no.4
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• pp.21-27
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• 2006

This paper is for the segmentation and volume calculation of the white matter and gray matter from brain MRI. We segment white matter, gray matter and CSF from the Brain image in the normal and abnormal person, and calculate the volume of segmented tissue. In this paper, we present a new method of extracting white matter, gray matter and CSF and calculation its volume from MR images for brain. And we have developed the determining method of threshold that can extract white matter and gray matter from MR image for brain through the analysis of gray values represented by ratio of each component. We proposed the calculation method of volume for white matter and gray matter by using number of extracted pixels in each slice. This algorithm input CSF/Head volume ratio and age of patient and calculates discriminant value through discriminant expression, classifies normal and abnormal using calculated discriminant value. As a result, we could blow that white matter and gray matter volume decrease and CSF volume increase as we grow gold.

• Investigative Magnetic Resonance Imaging
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• v.13 no.1
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• pp.22-30
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• 2009

Purpose : Patient motion during magnetic resonance (MR) imaging is one of the major problems due to its long scan time. Entropy based post-processing motion correction techniques have been shown to correct motion artifact effectively. One of main limitations of these techniques however is its long processing time. In this study, we propose several methods to reduce this long processing time effectively. Materials and Methods : To reduce the long processing time, we used the separability property of two dimensional Fourier transform (2-D FT). Also, a computationally light metric (sum of all image pixel intensity) was used instead of the entropy criterion. Finally, partial Fourier reconstruction, in particular the projection onto convex set (POCS) method, was combined thereby reducing the size of the data which should be processed and corrected. Results : Time savings of each proposed method are presented with different data size of brain images. In vivo data were processed using the proposed method and showed similar image quality. The total processing time was reduced to 15% in two dimensional images and 30% in the three dimensional images. Conclusion : The proposed methods can be useful in reducing image motion artifacts when only post-processing motion correction algorithms are available. The proposed methods can also be combined with parallel imaging technique to further reduce the processing times.

• 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.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.72-74
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• 1997

We have developed a 3-D image processing and display technique that include image resampling, modification of MIP, and fusion of MIP image and volumetric rendered image. This technique facilitates the visualization of the three-dimensional spatial relationship between vasculature and surrounding organs by overlapping the MIP image on the volumetric rendered image of the organ. We applied this technique to a MR brain image data to produce an MRI angiogram that is overlapped with 3-D volume rendered image of brain. MIP technique was used to visualize the vasculature of brain, and volume rendering was used to visualize the other structures of brain. The two images are fused after adjustment of contrast and brightness levels of each image in such a way that both the vasculature and brain structure are well visualized either by selecting the maximum value of each image or by assigning different color table to each image. The resultant image with this technique visualizes both the brain structure and vasculature simultaneously, allowing the physicians to inspect their relationship more easily. The presented technique will be useful for surgical planning for neurosurgery.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.216-224
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• 1997

In this paper, we propose a depth information extraction method for intermediate image synthesis. As stereo matching method, MBS(Multiple-Baseline Stereo) method has been proposed, in which the matching accuracy increases by using the multiple camera, but there are some inherent problems such as computational complexity, boundary overreach(BO) in depth map, and occlusion. So, we propose the modified version of MBS so called Multi-Resolution MBS(MR-MBS). Moreover, we also propose an adaptive occlusion area processing technique to improve the accuracy of the depth information in occlusion area.