• Journal of radiological science and technology
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• v.34 no.4
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• pp.323-331
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• 2011

We evaluated clinical usefulness of Arterial spin labeling perfusion MR imaging on the acute ischemic cerebral infarction patients through this study. We compared 22 patients who were done with DSC imaging and ASL imaging in admitted emergency room with acute ischemic cerebral infarction, with 36 normal comparison persons (DSC image on 21persons, ASL images on 15persons). Siemens Magnetom Verio 3.0T with 12 channel head coil was used for this study. DSC image obtained 4 maps(rCBV, rCBF, rMTT, TTP) through post-processing. For qualitative analysis we compared the area of lesion macro-diagonal with the size of diffusion weighted MR image for rMTT, TTP, rCBF, rCBV, ASL maps. For Quantitative analysis we analyzed significant correlations between less than 3 cm infarction group and normal comparison group using mean relative value of flowing image with Mann-Whitney U test. TTP(95.5%) and rCBF(95.5%) maps showed high recognition rate in qualitative analysis for >3cm infarction group. The rCBF and rCBV map tests were highly related with final stage stroke areas. Mean relative value of infarction group showed a significant correlations in quantitative analysis(p<0.05). As a conclusion, arterial spin labeling image showed high lesion recognition rate in the >3cm infarction group. Mean relative values in quantitative evaluation were used for reference data. If we do more sustainable researches, ASL image will be useful for an early diagnosis of cerebral infarction, determination of the range of ischemic pneumbra and effective treatments.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.696-701
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• 2002

This paper describes some results of change detection in Tokyo metropolitan area, Japan , using the Landsat TM data, and methods to quantify the ground cover classes. The changes are analyzed using the measures of not only conventional spectral classes but also a set of landscape indices to describe spatial properties of ground cove types using fractal dimension of objects, entropy in the specific windows defining the neighbors of focusing locations. In order eliminate the seasonal radiometric effects on TM data, an automated class labeling method is also attempted. Urban areas are also delineated automatically by defining the boundaries of the urban area. These procedures for urban change detection were implemented by the unified image computing methods proposed by the author, they can be automated in coherent and systematic ways, and it is anticipated to automate the whole procedures. The results of this analysis suggest that Tokyo metropolitan area was extended to the suburban areas along the new transportation networks and the high density area of Tokyo were also very much extended during the period between 1985 and 1995.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.951-956
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• 1990

The present paper describes a new technique for associating images employing a set of local constraints among pixels on an image. The technique describes the association problem in terms of consistent labeling which is an abstraction of various kinds of network constraints problems. In this particular research, a pixel and its gray value correspond to a unit and a label, respectively. Since constraints among units on an image are defined with respect to each n-tuple of pixels, performance of the present association technique largely depends on how to choose the n-tuples on an image plane. The main part of this paper is devoted to discussing this selection scheme and giving a solution to it as well as showing the algorithm of association. Also given are some results of the simulation performed on synthetic binary images to examine the performance of proposed technique, followed by the argument on further studies.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1093-1096
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• 1999

In this paper, video image segmentation algorithm based on color histogram and change detector is proposed. Color histograms are calculated from both changed region which is detected in the previous and current frame and unchanged region. With each histogram, modes and valleys are detected. Then, color vectors are calculated by averaging pixels in modes. Markers are extracted by labeling color vectors that represent modes, the watershed algorithm is applied to determine uncertain region. In growing region, the root mean square(RMS) of the distance between average pixel in marker region and adjacent pixel is used as a measure. The proposed algorithm based on color histogram and change detector segments video image fastly and effectively. And simulation results show that the proposed method determines the exact boundary between background and foreground.

• Proceedings of the CALSEC Conference
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• 2004.02a
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• pp.223-226
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• 2004

Several studies have shown that the trust is a significant barrier for realizing the potential of e-commerce. Trust is not only a short-term issue but also the most significant long-term barrier for realizing the potentials of e-commerce. Because digital contents which have been used in e-commerce are easy to be duplicated, the enforcement of digital copyright protection is an important issue. Watermarking is a technique for labeling digital pictures by hiding secret information in the image. In this paper, a discrete wavelet transform(DWT) based technique for embedding digital watermark into image is proposed. The performance of the proposed watermarking is robust to a variety of signal distortions, such as JPEG and image processing operations.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.60-61
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• 1998

In this paper, we propose an algorithm for automatic segmentation of 3-dimesional brain MR images. In order to segment 3-dimensional brain MR images, we start segmentation from a mid-sagittal brain MR image. Then the segmented mid-sagittal brain MR image is used as a mask that is applied to the remaining lateral slices. Then we apply preprocessing, which includes thresholding and region-labeling, to the lateral slices, resulting in simplified 3-D brain MR images. Finally, we remove remaining problematic regions in the 3-dimensional brain MR image using the connectivity-based thresholding segmentation algorithm. Experiments show satisfactory results.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.5
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• pp.83-93
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• 1998

Three dimensional data acquisition system based on the structured light is developed in this work. The system is composed of a CCD camera, slide projector, and various image processing programs. Calibration procedures and several image processing steps which are necessary to get the rnage data are described. A new grid labeling technique and a grid pattern are devised to improve the accuracy of th eobtained data. Preliminary experimental result shows that the developed system may be used as a simple and cheap 3D data acquisition system. Severla suggestions are included for further research.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.357-362
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• 1996

A way of quantitatively describing the tissue architecture we have investigated when developing a computer program for malignancy grading of transitional cell bladder carcinoma. The minimum spanning trees, MST was created by connecting the center points of the nuclei in the tissue section image. These nuclei were found by thresholding the image at an automatically determined threshold followed by a connected component labeling and a watershed algorithm for separation of overlapping nuclei. Clusters were defined in the MST by thresholding the edge lengths. For these clusters geometric and densitometric features were measures. These features were compared by multivariate statistical methods to the subjective grading by the pathologists and the resulting correspondence was 85% on a material of 40 samples.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.930-932
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• 2003

For this study we used a CCD video camera to capture the pavement image information via the computer. During investigation processing, the CCD video camera captured 10${\sim}$30 images per second. If the vehicle velocity is too fast, the collected images will be duplicated and if the velocity is too slow there will be a gapped between images. Therefore, in order to control the efficiency of the image grabber we should add accessory tools such as the Differential Global Positioning System (DGPS) and odometer. Furthermore, Kalman Filtering can also solve these problems. After the CCD video camera captured the pavement images, we used the Least-Squares method to eliminate images of gradation which have non-uniform surfaces due to the illumination at night. The Fuzzy Entropy method calculates images of threshold segments and creates binary images. Finally, the Object Labeling algorithm finds objects that are cracks or noises from the binary image based on volume pixels of the object. We used these algorithms and tested them, also providing some discussion and suggestions.

• Journal of Korea Multimedia Society
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• v.20 no.5
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• pp.740-747
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• 2017

A fast cell contour extraction method using CUDA parallel processing technique is presented. The cell contour extraction is one of important processes to analyze cell information in pathology. However, conventional sequential contour extraction methods are slow for a huge high-resolution medical image, so they are not adequate to use in the field. We developed a parallel morphology operation algorithm to extract cell contour more quickly. The algorithm can create an inner contour and fail to extract the contour from the concave part of the cell. We solved these problems by subdividing the contour extraction process into four steps: morphology operation, labeling, positioning and contour extraction. Experimental results show that the proposed method is four times faster than the conventional one.