• Journal of Korea Multimedia Society
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• v.10 no.7
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• pp.846-855
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• 2007

Significant feature extraction in cancer cell image analysis is an important process for grading cell carcinoma. In this study, we propose a method for 3D quantitative analysis of cell nuclei based upon digital image cytometry. First, we acquired volumetric renal cell carcinoma data for each grade using confocal laser scanning microscopy and segmented cell nuclei employing color features based upon a supervised teaming scheme. For 3D visualization, we used a contour-based method for surface rendering and a 3D texture mapping method for volume rendering. We then defined and extracted the 3D morphological features of cell nuclei. To evaluate what quantitative features of 3D analysis could contribute to diagnostic information, we analyzed the statistical significance of the extracted 3D features in each grade using an analysis of variance (ANOVA). Finally, we compared the 2D with the 3D features of cell nuclei and analyzed the correlations between them. We found statistically significant correlations between nuclear grade and 3D morphological features. The proposed method has potential for use as fundamental research in developing a new nuclear grading system for accurate diagnosis and prediction of prognosis.

• Journal of Life Science
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• v.30 no.4
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• pp.402-409
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• 2020

Nervous necrosis virus (NNV) contains a bi-segmented viral genome, RNA1 (3.4 kb, RdRp), and RNA2 (1.4 kb, capsid protein) in a small particle (25 nm). Despite its extremely compact size, NNV has caused serious damage by infecting approximately 120 fish species worldwide since it was first reported in the late 1980s. In order to minimize the damage caused by NNV infection and develop effective vaccines, it is necessary to understand the intra cellular signaling system according to NNV infection. NNV infection induces cell cycle arrest at the G1 phase via the p53-dependent pathway to use the cellular system for its replication. Otherwise, host cells recognize NNV infection through the RIG-1-like receptor (RLR) signaling pathway to control the virus and infected cells, and then ISGs required for antiviral action are activated via the IFN signaling pathway. Moreover, apoptosis of infected cells is triggered by the unfolded protein response (UPR) through ER stress and mitochondria-mediated cell death. Cell signaling studies on the NNV infection mechanisms are still at an early stage and many pathways have yet to be identified. Understanding the various disease-specific cellular signaling systems associated with NNV infection is essential for rapid and accurate diagnosis and vaccine development.

• BMB Reports
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• v.43 no.4
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• pp.279-283
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• 2010

Polydnavirus genome is segmented and dispersed on host wasp chromosome. After replication, the segments form double- stranded circular DNAs and embedded in viral coat proteins. These viral particles are delivered into a parasitized host along with parasitoid eggs. A serine-rich protein (SRP) is predicted in a polydnavirus, Cotesia plutellae bracovirus (CpBV), genome in its segment no. 33 (CpBV-S33), creating CpBV-SRP1. This study explored its expression and physiological function in the diamondback moth, Plutella xylostella, larvae parasitized by C. plutellae. CpBV-SRP1 encodes 122 amino acids with 26 serines and several predicted phosphorylation sites. It is persistently expressed in all tested tissues of parasitized P. xylostella including hemocyte, fat body, and gut. Its physiological function was analyzed by injecting CpBV-S33 and inducing its expression in nonparasitized P. xylostella by a technique called SERI (segment expression and RNA interference). The expression of CpBV-SRP1 significantly impaired the spreading behavior and total cell count of hemocytes of treated larvae. Subsequent RNA interference of CpBV-SRP1 rescued the immunosuppressive response. This study reports the persistent expression of CpBV-SRP1 in a parasitized host and its parasitic role in suppressing the host immune response by altering hemocyte behavior and survival.

• Archives of Plastic Surgery
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• v.41 no.5
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• pp.584-587
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• 2014

In the present study, a fibular osteotomy guide based on a computer simulation was applied to a patient who had undergone mandibular segmental ostectomy due to oncological complications. This patient was a 68-year-old woman who presented to our department with a biopsy-proven squamous cell carcinoma on her left gingival area. This lesion had destroyed the cortical bony structure, and the patient showed attenuation of her soft tissue along the inferior alveolar nerve, indicating perineural spread of the tumor. Prior to surgery, a three-dimensional computed tomography scan of the facial and fibular bones was performed. We then created a virtual computer simulation of the mandibular segmental defect through which we segmented the fibular to reconstruct the proper angulation in the original mandible. Approximately 2-cm segments were created on the basis of this simulation and applied to the virtually simulated mandibular segmental defect. Thus, we obtained a virtual model of the ideal mandibular reconstruction for this patient with a fibular free flap. We could then use this computer simulation for the subsequent surgery and minimize the bony gaps between the multiple fibular bony segments.

• Journal of Microbiology
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• v.34 no.2
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• pp.124-130
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• 1996

A survey was conducted to determine the prevalance of infectious pancreatic necrosis virus (IPNV) on fish farms in Korea and the epidemiology of IPNV infection in the farmed rainbow trout. In total, 43 pools of rainbow trout with apparent signs of viral infection from five provinces were obtained and analyzed. Evident cytopathic effects, including karyopycnosis and cell destruction, were observed in CHSE (chinook samlmon embyro)-214 cells infected with the virus isolates. Of these, ten viral isolates were assumed to be IPNV based on biophysical properties. RNA analysis revealed that the isolates contained two-segmented RNA genomes, further indicating that the viral isolates are IPNV. Antigenic comparison of the IPNV isolates identified three distinct serological groups separable by the cross-neutralization test. Of the ten IPNV isolates, six could be classified as strain DRT, two as strain Ab, and two as strain VR299. We were not able to isolate new strain of IPNV or any isolate serologically similar to the standard strain Sp.poraceae and families of the Agaricales, they are genetically more related to the Polyporaceae. These results are consistent with morphological characters observed in those mushrooms. However, it is premature to conclude taxonomic status Ganoderma species in the present study employing small sample size.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.7
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• pp.57-65
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• 2002

In this paper, a 2.5V 10-bit 300MSPS CMOS D/A Converter is described. The architecture of the D/A Converter is based on a current steering 8+2 segmented type, which reduces non-linearity error and other secondary effects. In order to achieve a high performance D/A Converter, a novel current cell with a low spurious deglitchnig circuit and a novel inverse thermomeer decoder are proposed. To verify the performance, it is integrated with $0.25{\mu}m$ CMOS 1-poly 5-metal technology. The effective chip area is $1.56mm^2$ and power consumption is about 84mW at 2.5V power supply. The simulation and experimental results show that the glitch energy is 0.9pVsec at fs=100MHz, 15pVsec at fs=300MHz in worst case, respectively. Further, both of INL and DNL are within ${\pm}$1.5LSB, and the SFDR is about 45dB when sampling, frequency, is 300MHz and output frequency is 1MHz.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.167-174
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• 2008

The introduction of confocal microscopy makes it possible to observe the structural change of live neuronal cell. Neuro-degenerative disease, such as Alzheimer;s and Parkinson’s diseases are especially related to the morphological change of dendrite spine. That’s the reason for the study of segmentation and extraction from confocal microscope image. The difficulty comes from uneven intensity distribution and blurred boundary. Therefore, the image processing technique which can overcome these problems and extract the structural information should be suggested. In this paper, we propose robust structural information extracting technique with confocal microscopy images of dendrite in brain neurons. First, we apply the nonlinear diffusion filtering that enhance the boundary recognition. Second, we segment region of interest using iterative threshold selection. Third, we perform skeletonization based on Fast Marching Method that extracts centerline and boundary for analysing segmented structure. The result of the proposed method has been less sensitive to noise and has not been affected by rough boundary condition. Using this method shows more accurate and objective results.

• Journal of Veterinary Science
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• v.25 no.4
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• pp.55.1-55.12
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• 2024

Importance: Neonatal calf diarrhea is a major cause of mortality in newborn calves worldwide, posing a significant challenge in bovine herds. Group A Bovine Rotaviruses (BRVA) are the primary contributors to severe gastroenteritis in calves under two months old. Objectives: This study examined the prevalence and molecular characterization of BRVA in neonatal calves in Gujarat, India. Methods: Sixty-nine diarrheic fecal samples were collected and subjected to various molecular methods of BRVA detection, isolation, and characterization. Results: The latex agglutination test (LAT), electropherotyping (RNA-PAGE), and reverse transcription polymerase chain reaction revealed positivity rates of 39.13%, 20.30%, and 37.70%, respectively. RNA-PAGE identified 11 bands with a 4:2:3:2 migration pattern, indicative of the segmented genome of BRVA. BRVA was successfully isolated from LATpositive samples, with 26 samples exhibiting clear cytopathic effects upon passage in MA-104 cell lines. Genotyping identified G10 as the predominant G genotype, with P[11] genotypes comprising 76.92% of the isolates. The most common G/P combination was G10P[11], highlighting its zoonotic potential. Conclusions and Relevance: These findings underscore the importance of molecular detection and genotyping for effective vaccine development. This study provides crucial insights into the prevalent G and P genotypes of BRVA in Gujarat, India, aiding in the development of targeted control measures.

• Journal of Internet Computing and Services
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• v.10 no.6
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• pp.99-111
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• 2009

The result of Image segmentation, an indispensable process in image processing, significantly affects the analysis of an image. Despite the significance of image segmentation, it produces some problems when the variation of pixel values is large, or the boundary between background and an object is not clear. Also, these problems occur frequently when many objects in an image are placed very close by. In this paper, when the shape of objects in an image is circular, we proposed an algorithm which segment an each object in an image using the geometric characteristic of circular shape. The proposed algorithm is composed of 4 steps. First is the boundary edge extraction of whole object. Second step is to find the candidate points for further segmentation using the boundary edge in the first step. Calculating the representative circles using the candidate points is the third step. Final step is to draw the line connecting the overlapped points produced by the several erosions and dilations of the representative circles. To verify the efficiency of the proposed algorithm, the algorithm is compared with the three well-known cell segmentation algorithms. Comparison is conducted by the number of segmented region and the correctness of the inner segment line. As the result, the proposed algorithm is better than the well-known algorithms in both the number of segmented region and the correctness of the inner segment line by 16.7% and 21.8%, respectively.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.2
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• pp.28-36
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• 2022

As port structures are exposed to various extreme external loads such as wind (typhoons), sea waves, or collision with ships; it is important to evaluate the structural safety periodically. To monitor the port structure, especially the rubber fender, a fender segmentation system using a vision sensor and deep learning method has been proposed in this study. For fender segmentation, a new deep learning network that improves the encoder-decoder framework with the receptive field block convolution module inspired by the eccentric function of the human visual system into the DenseNet format has been proposed. In order to train the network, various fender images such as BP, V, cell, cylindrical, and tire-types have been collected, and the images are augmented by applying four augmentation methods such as elastic distortion, horizontal flip, color jitter, and affine transforms. The proposed algorithm has been trained and verified with the collected various types of fender images, and the performance results showed that the system precisely segmented in real time with high IoU rate (84%) and F1 score (90%) in comparison with the conventional segmentation model, VGG16 with U-net. The trained network has been applied to the real images taken at one port in Republic of Korea, and found that the fenders are segmented with high accuracy even with a small dataset.