• Applied Microscopy
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• v.28 no.2
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• pp.225-236
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• 1998

Adriamycin is a one of anthracyclin antibiotics isolated from the culture media of Streptomyces peucetius var casius. The formation of reactive oxygen metabolite by redox cycling during the metabolism and the inhibition of DNA synthesis results in antineoplastic effects of adriamycin. The authors have demonstrated the effects of SOD(superoxide dismutase) or DMTU (dimethyl thiourea), which are used as an antioxidant, on the ultrastructural changes of the gastric chief cells after the administration of adriamycin in the rat. Adriamycin (30 mg/kg) was administered intraperitoneally to the Sprague-Dawley rats weighing about 220 gm and SOD (15000 unit/kg) or DMTU (500 mg/kg) were administered intraperitoneally to the rats 30 minutes after the administration of adriamycin. The gastric chief cells 24, 48 and 72 hours after the administration of adriamycin were observed with Hitachi-600 electron microscope. The results were as follows. 1. SOD or DMTU alone did not affect the ultra structures of the gastric chief cells in the rat. 2. Dilation, sacculation and segmentation of the cisternae of rough endoplasmic reticulum, dilation of the saccules of Golgi complex and dilated mitochondria with electron lucent matrix were seen in the adriamycin treated rats. In the course of time, the ultrastructures of the chief cell changed markedly. 72 hours after drug administration, severely dilated cisternae of rough endoplasmic reticulum, with clumping of chromatin around the nuclear envelope and mitochondria with electron lucent matrix and dilated cristae were seen in the chief cell. 3. The treatment of SOD is more effective than DMTU to attenuated the ultrastructural changes of the chief cells in the adriamycin administered rat. Consequently it is suggested that adriamycin would induce the degenerative changes of the organelles of the chief cell. The treatment of SOD is more effective than DMTU to attenuate the adriamycin induced damage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.6
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• pp.1153-1158
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• 2006

The classification of the background and cell areas is very important research area because of the ambiguous boundary. In this paper, the region of cell is extracted from an image of uterine cervical cytodiagnosis using the region growing method that increases the region of interest based on similarity between pixels. Segmented image from background and cell areas is binarized using a threshold value. And then 8-directional tracking algorithm for contour lines is applied to extract the cell area. First, the extracted nucleus is transformed to RGB color that is the original image. Second, the K-means clustering algorithm is employed to classify RGB pixels to the R, G, and B channels, respectively. Third, the Hue information of nucleus is extracted from the HSI models that is the transformation of the clustering values in R, G, and B channels. The backpropagation algorithm is employed to classify and identify the normal or abnormal nucleus.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.4
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• pp.335-342
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• 2012

3D point cloud is widely used in Architecture, Civil Engineering, Medical, Computer Graphics, and many other fields. Due to the improvement of 3D laser scanner, a massive 3D point cloud whose gigantic file size is bigger than computer's memory requires efficient preprocessing and visualization. We suggest a data structure to solve the problem; a 3D point cloud is gradually subdivided by arbitrary-sized cube grids structure and corresponding point cloud subsets generated by the center of each grid cell are achieved while preprocessing. A massive 3D point cloud file is tested through two algorithms: QSplat and ours. Our algorithm, grid-based, showed slower speed in preprocessing but performed faster rendering speed comparing to QSplat. Also our algorithm is further designed to editing or segmentation using the original coordinates of 3D point cloud.

• Korean Journal of Plant Tissue Culture
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• v.22 no.6
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• pp.323-327
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• 1995

This experiment was carried out to observe the origin and developmental pattern of somatic embryos of Oenanthe javanica ($B^{L}.$) DC. The experiment included observation of embryogenic cells and their development stages by light microscope, transmission electron microscope and scanning electron microscope. The embryogenic cells, which were smaller than non-embryogenic cells in size with expanded nucleus and dense cytoplasm. When stained with hematoxylin, the embryogenic cells were readily distinguished from the non-embryogenic cells of which cell walls were stained with safranin. It was observed at somatic embryos developed from single cells on the epidermis of developing embryos or in the surface or inside of embryogenic clumps by segmentation pattern. Observation with a transmission electron microscope revealed that the embryogenic cells had dense cytoplasm expanded nucleus, small vacuoles, large amyloplasts containing starch grains, and abundant organelles including lipid bodies. Under a scanning electron microscope, embryogenic callus was shown to consist of very smaller cells than non-embryogenic cells in an orderly arrangement and covered with a net-like structure, while the non-embryogenic callus consisted of large cells, irregular in size and arrangement, and covered with a gelatin-like material.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11A
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• pp.891-897
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• 2009

In the satellite communications, the frequency sharing with other services is important because the service coverage is generally very wide and overlaps with those of other wireless services. This paper introduces a new technique to mitigate interference into the terrestrial stations from the Earth station in the same frequency band by means of band segmentations which are portions of the overall operation frequency band divided by frequency reuse factor. We consider a multi-beam satellite system, where frequency bands are reused in each satellite cell. The terrestrial stations use band segmentations of adjacent satellite cells, and this may decrease the interferences. By this way, the terrestrial and satellite systems can share the same frequency bands efficiently. The simulation is performed at frequency reuse factors, seven and three. The simulation results show that the proposed method can highly reduce the interference level to -168 dBW or -163 dBW depending on the considered frequency reuse factor from -117 dBW at the 90% link availability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3708-3728
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• 2021

Indian herbal plants are used in agriculture and in the food, cosmetics, and pharmaceutical industries. Laboratory-based tests are routinely used to identify and classify similar herb species by analyzing their internal cell structures. In this paper, we have applied computer vision techniques to do the same. The original leaf image was preprocessed using the Chan-Vese active contour segmentation algorithm to efface the background from the image by setting the contraction bias as (v) -1 and smoothing factor (µ) as 0.5, and bringing the initial contour close to the image boundary. Thereafter the segmented grayscale image was fed to a leaky capacitance fired neuron model (LCFN), which differentiates between similar herbs by combining different groups of pixels in the leaf image. The LFCN's decay constant (f), decay constant (g) and threshold (h) parameters were empirically assigned as 0.7, 0.6 and h=18 to generate the 1D feature vector. The LCFN time sequence identified the internal leaf structure at different iterations. Our proposed framework was tested against newly collected herbal species of natural images, geometrically variant images in terms of size, orientation and position. The 1D sequence and shape features of aloe, betel, Indian borage, bittergourd, grape, insulin herb, guava, mango, nilavembu, nithiyakalyani, sweet basil and pomegranate were fed into the 5-fold Bayesian regularization neural network (BRNN), K-nearest neighbors (KNN), support vector machine (SVM), and ensemble classifier to obtain the highest classification accuracy of 91.19%.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.533-535
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• 1999

자궁경부진 세포인식 시스템에 있어서 가장 중요한 것이 영상처리를 이용하여 세포핵과 세포질을 추출하여 세포의 형태적인 정보를 알아내는 과정이다. 기존의 전역 thresholding 기법이나 region growing의 경우는 pap smear 검사를 통해 얻어진 세포 영상을 분할할 수 있는 region growing 기법을 제안한다. 제안된 region growing 기법은 초기에 seed를 검출할 때 local threshold growing 기법을 제안한다. 제안된 region growing 기법은 초기에 seed를 검출할 때 local threshold 개념을 도입하여 seed의 검출을 고르게 하고, 2가지 확장 조건을 사용하여 영역을 확장한다. 첫 번째 확장 조건은 비정상 세포나 artifact가 많아서 어둡게 나타나는 영상이나 세포질과 배경의 경계가 뚜렷하지 않아서 세포질의 구별이 어려운 영상의 영역 분할이 가능하도록 그 특성을 반영하고, 두 번째 조건은 세포가 흡수하는 빛의 양이 일정하다는 가정으로 영상에서의 지역 특성(gray level, color 등을 반영한다. 제안된 기법은 정상세포 영상뿐만 아니라 비정상 세포 영상에 대하여 over-segment나 under-segment하는 경우를 줄여서 영역 분할에 좋은 결과를 보인다.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.422-424
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• 1999

본 논문에서는 질감 특징과 신경회로망을 이용한 유방암조직영상의 분할 방법을 제안한다. 신경회로망의 입력 노드에 사용될 질감 특징을 얻기 위해 10개의 영상에 대해 각 영역(양성세포핵, 음성세포핵, 배경)에서 10개씩의 화소를 선택하고, 그 화소를 중심으로 하는 5$\times$5 영역 30개를 획득, 총 300개의 영역에 대해 R, G, B 각각의 밴드에서 18개의 질감특징을 추출한다. 54개의 입력노드, 28개의 은닉노드, 3개의 출력노드의 구조를 가진 신경회로망을 구성하고, 역전파 학습 알고리즘을 사용하여 신경회로망을 최대오차율이 10-3보다 작을 때까지 학습시킨다. 학습에 의해 획득되어진 분류기를 이용하여 유방암 조직 세포영상을 양성세포핵, 음성세포핵, 배경부분으로 자동 분할한다.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.419-421
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• 1999

본 논문은 자궁경부암 검사를 위한 전처리 과정인 자궁경부암 세포 영상분할 문제 연구의 결과이다. 자궁경부암 세포 영상은 배경과 세포질 및 세포핵의 구별이 어렵다. 게다가 자궁경부암 검사 시스템은 짧은 시간동안 많은 영상을 처리해야 하기 때문에, 영상의 분석 속도가 빠르고 강력한 영상 분할 기법이 필요하다. 이를 위하여 우리는 thresholding 기법을 연구하였다. 먼저 세포 영상의 각 화소의 명암의 분포를 조사하여 히스토그램을 구하였다. 히스토그램은 0~255 사이에 존재하게 되는데, 0~255의 전 영역에 존재하기 보다는 그 중 일부분에만 존재한다. 우리는 히스토그램이 존재하는 영역을 백분율로 나누고 세포핵 및 세포질이 존재하는 영역의 분포를 구하여 global threshold를 찾았고, 이를 기준으로 각 점을 thresholding 할 때에 주위의 평균값을 보정값으로 두어 local thresholding을 수행하였다. 결과 영상은 핵의 영역을 탐색하기 위한 seed로 사용하기에 적합하다.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06b
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• pp.296-299
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• 2011

임상 진단에서 환자의 의료 영상을 시각적으로 보고 해석하거나 또는 수작업으로 영상을 해석하여 진단에 이용한다. 이러한 수작업의 불편함을 해소하기 위하여 의료 영상처리 알고리즘들이 많이 연구되어오고 있다. 그 중 영상처리의 정확도 부분이 많은 문제가 되고 있는데, 특히 세포영상에서는 인접한 영역의 분할이 가장 중요시되고 있다. 본 논문은 이러한 인접영역의 분할을 위해 객체의 기하 정보인 곡률(Curvature) 정보와 컨벡스 헐(Convex Hull)을 통한 분할 방법을 제안하고자 한다. 실험 결과 87.5%의 정확도가 검출되었으며 향후 인접 객체의 내부정보까지 고려한 효과적인 분할 방법을 연구하고자 한다.