• Proceedings of the Korean Information Science Society Conference
• /
• 1999.10b
• /
• pp.419-421
• /
• 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 Institute of Information and Commucation Sciences Conference
• /
• 2006.05a
• /
• pp.335-339
• /
• 2006

자궁 경부 세포진 영상의 핵 영역 분할은 자궁 경부암 자동화 검색 시스템의 가장 어렵고도 중요한 분야로 알려져 있다. 자궁 경부 세포진 영상은 배경과 세포의 영역이 확실히 구분되지 않는 경우가 많기 때문에 이들을 확실히 구분하는 것이 매우 중요하다. 본 논문에서는 이러한 문제점을 해결하기 위해 자궁 경부 세포진 영상에서 Region growing 기법을 적용하여 세포 영상을 분할한다. Region growing 기법은 화소간의 유사도를 측정하여 영역을 확장하여 분할하는 방법이다. 세포와 배경이 분할된 영상을 일정 임계값을 이용하여 영상을 이진화 한 후, 8방향 윤곽선 추적 알고리즘을 이용해 세포 영역을 추출한다. 추출된 세포 영역을 원 영상인 RGB 컬러로 변환한 후에 K-means 알고리즘을 적용하여 각 세포 영역의 RGB 화소를 R, G, B 채널로 각각 분리하여 클러스터링한다. 클러스터링된 각각의 R, G, B 채널의 클러스터 값을 이용하여 HSI 모델로 변환시킨 후에 세포핵 영역의 Hue 정보를 추출한다. 추출된 세포핵의 특징을 오류 역전파 알고리즘을 적용하여 정상 세포와 비정상 세포를 분류하고 인식한다.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.5
• /
• pp.519-524
• /
• 2006

Segmentation for the region of nucleus in the image of uterine cervical cytodiagnosis is known as the most difficult and important part in the automatic cervical cancer recognition system. In this paper, the region of nucleus is extracted from an image of uterine cervical cytodiagnosis using the fuzzy grey morphology operation. The characteristics of the nucleus are extracted from the analysis of morphemetric features, densitometric features, colormetric features, and textural features based on the detected region of nucleus area. The classification criterion of a nucleus is defined according to the standard categories of the Bethesda system. The enhanced fuzzy ART algorithm is used to the extracted nucleus and the results show that the proposed method is efficient in nucleus recognition and uterine cervical Pap-Smears extraction.

• The Journal of the Korea Contents Association
• /
• v.11 no.5
• /
• pp.84-92
• /
• 2011

The automated segmentation technique of cell region in Bio Images helps biologists understand complex functions of cells. It is mightly important in that it can process the analysis of cells automatically which has been done manually before. The conventional methods for segmentation of cell and nuclei from multi-channel images consist of two steps. In the first step nuclei are extracted from DNA channel, and used as initial contour for the second step. In the second step cytoplasm are segmented from Actin channel by using Active Contour model based on intensity. However, conventional studies have some limitation that they let the cell segmentation performance fall by not considering inhomogeneous intensity problem in cell images. Therefore, the paper consider correlation between DNA and Actin channel, and then proposes the preprocessing algorithm by which the brightness of cell inside in Actin channel can be compensated homogeneously by using DNA channel information. Experiment result show that the proposed preprocessing method improves the cell segmentation performance compared to the conventional method.

• Journal of Embryo Transfer
• /
• v.16 no.3
• /
• pp.213-221
• /
• 2001

This study was conducted to examine in vitro developmental ability of porcine embryos after somatic cell nuclear transfer. The porcine ear fell was cultured in vitro for confluency in serum-starvation condition(TCM-199 + 0.5% FBS) far 3~6 days of cell confluency. The zona pellucida of IVM oocytes were partially drilled using laser system. Single somatic cell was individually transferred into enucleated oocytes. And the reconstructed embryos were electrically fused(single DC 1.9kv/cm, 30$\mu$ sec) with 0.3M mannitol. After electrofusion, embryos were activated(single AC 5v/mm, 5sec) and cultured in HCSU-23 medium containing 10% FBS at 39$^{\circ}C$, 5% $CO_2$ in air for 6 to 8 days. The fusion rate of donor cells was 45.6, 36.8 and 46.1% in 3~4, 5~6 days of serum starvation and non serum starvation(N-S), and were 52.7. 53.0 and 51.7% in 1~2. 5~6 and 13~14 passages of donor cell culture, respectively. No significant difference was found in the fusion rate of donor cells by the duration of serum starvation treatment or the number of donor cell passages. By the size of donor cells, however, the fusion rate was significantly higher(P<0.05) for reconstructed embryos derived from 25r $\mu$m $\geq$ site of donor cells (65.3%) than that of 25~30$\mu$ m(42.5%) or 30$\mu$ m(45.5%)$\leq$ cells. The cleavage rate was significantly (P<0.05) higher in 3~4 darts of serum starvation treatment(67.1%) than that in N-S (50.7%) or 5~6 days of starvation(57.1%). The activation rate by the size of donor cells in fused oocytes was 56.5, 68.8 and 58.5%, respectively, and was not significant.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.6
• /
• pp.1153-1158
• /
• 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 Korea Institute of Information and Communication Engineering
• /
• v.11 no.10
• /
• pp.1992-1998
• /
• 2007

It is important to obtain conn cytodiagnosis to classify background, cytoplasm, and nucleus from the diagnostic image. This study mose an algorithm that detects and classifies carcinoma cells of the uterine cervix in Pap smear using features of cervical cancer. It applies Median filter and Gaussian filter to get noise-removed nucleus area and also applies Kapur method in binarization of the resultant image. We apply 8-directional contour tracking algorithm and stretching technique to identify and revise clustered cells that often hinder to obtain correct analysis. The resulted nucleus area has distinguishable features such as cell size, integration rate, and directional coefficient from normal cells so that we can detect and classify carcinoma cells successfully. The experiment results show that the performance of the algorithm is competitive with human expert.

• Proceedings of the KSAR Conference
• /
• 2002.06a
• /
• pp.35-35
• /
• 2002

본 연구는 핵이식 기법을 이용하여 고능력 한우의 대량 생산기술을 개발하기 위하여 수행하였다. Donor cell 은 축산기술연구소 남원지소에서 사육, 검정하고 있는 축군에서 육량 육질 국내 100위 이내의 암소에서 귀세포를 채취하여 동결 및 계대배양하여 사용하였다. 도축장에서 채취한 난소에서 난자를 채취하여 22시간 성숙 배양한 후 난구세포를 제거하고, 극체가 존재하는 난자를 선별하여 recipient cytoplasm으로 사용하였다. (중략)

• Korean Journal of Animal Reproduction
• /
• v.23 no.3
• /
• pp.271-278
• /
• 1999

This study was conducted to investigate the cytogenetic properties, in vitro development, and their relationship in the bovine reconstituted embryos following cell cycle-controlled nuclear transfer. Sixteen-cell stage embryos were treated by nocodazole, and after release from nocodazole treatment, their blastomeres were separated and allowed to subsequent cleavage. Blastomeres within 1.5 h post cleavage(hpc) and at 3hpc were transferred to enucleated oocytes at MII-phase or S-phase. Donor nuclei transferred into M II-phase recipients underwent various nuclear remodeling, such as extrusion of a polar body(PB)-like structure, premature chromosome condensation(PCC) and chromatin modifications. These nuclear remodeling patterns varied by the time post cleavage of donor blastomeres. Developmental rate to the blastocyst stage differed with time post cleavage of donor blastomeres and existence of a PB-like structure. Whereas do-nor nuclei transferred into S-phase oocytes did not undergo PCC and other major modifications, and their developmental potentials less depended on the nuclei types. This result confirms that the nuclear remodeling type differs with donor and recipient cell cycle stage, which affect the development of reconstituted bovine embryos.

• The Journal of the Korea Contents Association
• /
• v.10 no.4
• /
• pp.19-27
• /
• 2010

In recent years, high-throughput genome-wide RNA interference screening is emerging as an essential tool to biologists in understanding complex cellular processes. The manual analysis of the large number of images produced in each study spends much time and the labor. Hence, automatic cellular image analysis becomes an urgent need, where segmentation is the first and one of the most important steps. However, those factors such as the region overlapping, a variety of shapes, and non-uniform local characteristics of cellular images become obstacles to efficient cell segmentation. To avoid the problem, a new watershed-based cell segmentation algorithm using a localized segmentation method and a feature vector is proposed in this paper. Localized approach in segmentation resolves the problems caused by a variety of shapes and non-uniform characteristics. In addition, the poor performance of segmentation in overlapped regions can be improved by taking advantage of a feature vector whose component features complement each other. Simulation results show that the proposed method improves the segmentation performance compared to the method in Cellprofiler.