• Korean Journal of Head & Neck Oncology
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• v.26 no.2
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• pp.204-211
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• 2010

Background and Objectives : Boundary detection and drawing are essential in 3D reconstruction of neck mass. Manual tracing methods are popular for drawing head and neck tumor. To improve manual tracing, circular boundaries overlapping was tried. Materials and Methods : Twenty patients with neck tumors were recruited for study. Representative frames were examined for shapes of outline. They were all single closed curves. Circular boundaries were added to fill the outlines of the tumors. Inserted circles were merged to form single closed curves(Circular boundary overlapping, CBO). After surface rendering, 3 dimensional images with volumes and area data were made. Same procedures were performed with manual tracing from same cases. 3D images were compared with surgical photographs of tumors for shape similarity by 2 doctors. All data were evaluated with Mann-Whitney test(p<0.05). Results : Shapes of boundaries from CBO were similar with boundaries from manual tracing. Tumor outlines could be filled with multiple circular boundaries., While both boundary tracing gave same results in small tumors, the bigger tumors showed different data. Two raters gave the similar high scores for both manual and CBO methods. Conclusion : Circular boundary overlapping is time saver in 3 dimensional reconstruction of CT images.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2313-2319
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• 2020

The goal of this project is to achieve an accurate segmentation of the pulmonary tumors besides shortening the time and increasing the accuracy. Here, improved region growing (IRG) algorithm is introduced in order to segment the lung tumor with a sufficient accuracy in a shorter time compared to the other basics methods. This comprehensive algorithm was applied on 4 patients CT images and the results of the various steps on segmentation improvement shown 98% accuracy as compared to the basic algorithm. The combination of "multipoint growth start" produced a desirable outcome in accurately bounding the tumor. The proposed algorithm improved tumor identification by less than 13% along with a sufficient percentage of compliance accuracy.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.23
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• pp.10509-10512
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• 2015

Objective: To investigate the differential features of CT images in children with neuroblastomas (N) and ganglioneuroblastomas (G). Materials and Methods: Clinical data of 12 children in group G and 15 in group N undergoing CT examination and definitely diagnosed by pathology were retrospectively analyzed. The focal conditions were observed and compared in the two groups, including location, size, boundaries, morphology, enhanced degree and mode, abdominal vascular involvement, presence or absence of spanning the midline, infiltration of peripheral organs, angiography manifestations in tumors or surroundings, presence or absence of calcification and vascular tumor emboli as well as metastases of distal organs and lymph nodes. Results: In group N, the incidence of tumors in the adrenal area was conspicuously higher than in group G (P<0.05), while that of tumors with regular morphology and clear boundaries was significantly lower than in group G (P<0.01); Angiography manifestation rate and incidences of vascular embedding, lymph node metastasis, infiltration and organic metastasis in group N were all markedly higher than in group G (P<0.05). There was no statistical significance between the two groups in terms of focal size, presence or absence of calcification and spanning the midline, and enhanced degree and mode, as well as vascular tumor emboli (P>0.05). Conclusions: Mostly located in adrenal areas and with vascular embedding as a primary manifestation, the neuroblastoma extremely readily metastases to lymph nodes and other organs as well as infiltrating local tissues, with dilation on angiography frequent in or around the tumors. With vascular displacement as a primary manifestation, ganglioneuroblastoma has a regular morphology and clear boundaries.

• International Journal of Control, Automation, and Systems
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• v.2 no.1
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• pp.100-106
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• 2004

In this paper, we present a novel, rapid approach for the detection of brain tumors and deformity boundaries in medical images using a genetic algorithm with wavelet based preprocessing. The contour detection problem is formulated as an optimization process that seeks the contour of the object in a manner of minimizing an energy function based on an active contour model. The brain tumor segmentation contour, however, cannot be detected in case that a higher gradient intensity exists other than the interested brain tumor and deformities. Our method for discerning brain tumors and deformities from unwanted adjacent tissues is proposed. The proposed method can be used in medical image analysis because the exact contour of the brain tumor and deformities is followed by precise diagnosis of the deformities.

• The Korean Journal of Cytopathology
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• v.18 no.2
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• pp.157-160
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• 2007

Granular cell tumor (GCT) of the breast is a rare clinical entity, and is believed to be of schwannian origin and to follow a benign clinical course. A 50-year-old woman presented with a slowly growing mass in the right breast. Fine needle aspiration cytology revealed a cellular smear containing isolated or clustered cells showing round to oval nuclei with abundant oncocytic granular cytoplasm. Nuclei showed a fine granular chromatin pattern and occasional small single nucleoli. Cell boundaries were poorly defined, and naked nuclei were frequently found, Histologically, the tumor showed features of typical GCT, and immunohistochemical staining findings strongly supported the diagnosis. The present study demonstrates that GCT of the breast can mimic malignant lesions of breast both clinically and radiologically. The recognition of its cytologic features and suspicion of this lesion would undoubtedly aid the correct diagnosis of mammary GCT.

• Proceedings of the Korean Society of Medical Physics Conference
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• 1999.11a
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• pp.149-150
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• 1999

• Korean Journal of Veterinary Research
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• v.36 no.1
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• pp.143-150
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• 1996

Tumor masses from a Bengal tiger (Panthera tigris) of 13 years in age raised at the natural farm in Yong-In were examined grossly and microscopically. The tumors were observed in the subcutis, lung, heart, liver, pancreas, kidney, cecum and spleen. Histologically the tumors were composed of solid anaplastic cells that formed mature or immature small blood vessels and invaded the adjacent parenchyma. The nuclei of the tumor cells were large, vacuolated, and round or ovoid, sometimes dense and ovoid or spindle. The mitotic figures were common and the boundaries between the cells were indistinct. The stroma was very sparse. A diagnosis of this case was made as hemangiosarcoma on the basis of gross and microscopic features.

• Journal of Biomedical Engineering Research
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• v.43 no.5
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• pp.341-352
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• 2022

Medical image segmentation is the most important task in radiation therapy. Especially, when segmenting medical images, the liver is one of the most difficult organs to segment because it has various shapes and is close to other organs. Therefore, automatic segmentation of the liver in computed tomography (CT) images is a difficult task. Since tumors also have low contrast in surrounding tissues, and the shape, location, size, and number of tumors vary from patient to patient, accurate tumor segmentation takes a long time. In this study, we propose a method algorithm for automatically segmenting the liver and tumor for this purpose. As an advantage of setting the boundaries of the tumor, the liver and tumor were automatically segmented from the CT image using the 2D CoordConv DeepLab V3+ model using the CoordConv layer. For tumors, only cropped liver images were used to improve accuracy. Additionally, to increase the segmentation accuracy, augmentation, preprocess, loss function, and hyperparameter were used to find optimal values. We compared the CoordConv DeepLab v3+ model using the CoordConv layer and the DeepLab V3+ model without the CoordConv layer to determine whether they affected the segmentation accuracy. The data sets used included 131 hepatic tumor segmentation (LiTS) challenge data sets (100 train sets, 16 validation sets, and 15 test sets). Additional learned data were tested using 15 clinical data from Seoul St. Mary's Hospital. The evaluation was compared with the study results learned with a two-dimensional deep learning-based model. Dice values without the CoordConv layer achieved 0.965 ± 0.01 for liver segmentation and 0.925 ± 0.04 for tumor segmentation using the LiTS data set. Results from the clinical data set achieved 0.927 ± 0.02 for liver division and 0.903 ± 0.05 for tumor division. The dice values using the CoordConv layer achieved 0.989 ± 0.02 for liver segmentation and 0.937 ± 0.07 for tumor segmentation using the LiTS data set. Results from the clinical data set achieved 0.944 ± 0.02 for liver division and 0.916 ± 0.18 for tumor division. The use of CoordConv layers improves the segmentation accuracy. The highest of the most recently published values were 0.960 and 0.749 for liver and tumor division, respectively. However, better performance was achieved with 0.989 and 0.937 results for liver and tumor, which would have been used with the algorithm proposed in this study. The algorithm proposed in this study can play a useful role in treatment planning by improving contouring accuracy and reducing time when segmentation evaluation of liver and tumor is performed. And accurate identification of liver anatomy in medical imaging applications, such as surgical planning, as well as radiotherapy, which can leverage the findings of this study, can help clinical evaluation of the risks and benefits of liver intervention.

• Journal of Biomedical Engineering Research
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• v.41 no.2
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• pp.67-74
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• 2020

Brain tumors or gliomas are fatal cancer species with high recurrence rates due to their strong invasiveness. Therefore, the goal of surgery is complete tumor resection. However, the surgery is difficult to distinguish the border because tumors and blood vessels have the same color tone and shape. The fluorescein sodium is used as a fluorescence contrast agent for boundary separation. When the external light source is irradiated, yellow fluorescence is expressed in the tumor, which helps distinguish between blood vessels and tumor boundaries. But, the fluorescence expression of fluorescence sodium depends on the concentration of fluorescein sodium and such analytical data is insufficient. The unclear fluorescence can obscure the boundaries between blood vessels and tumors. In addition, reduce the efficiency of fluorescence sodium use. This paper proposes a protocol of concentration range for fluorescence expression conditions. Fluorescent expression was observed using a near-infrared (NIR) color camera with corresponding dilution using normal saline in 1 ml microtube. The flunoresence emission density range is 1.00 mM to 0.15 mM. The fluorescence emission begin to 1.00 mM and the 0.15 mM discolor. The discolor is difficult to fluorescence emission condition obserbation. Thus, the maximum density range of the bright fluoresecein is 0.15 mM to 0.30 mM. When the concentration range of fluorescein sodium is analyzed based on the gradient of fluorescence expression and the power measurement, the brightest fluorescence is expected to facilitate the complete resection of the tumor. For the concentration range protocol, setting concentration ranges and analyzing fluorescence expression image according to saturation and brightness to find optimal fluorescence concentration are important. Concentration range protocols for fluorescence expression conditions can be used to find optimal concentrations of substances whose expression pattern varies with concentration ranges. This study is expected to be helpful in the boundary classification and resection of brain tumors and glioma.

• Korean Journal of Veterinary Research
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• v.35 no.2
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• pp.375-381
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• 1995

Two intraocular tumors were identified in low and medium dosed groups of a carcinogenicity study using 200 males and 200 females Sprague-Dawley rats in Screening & Toxicology Research Center, Korea Research Institute of Chemical Technology. The tumors were grossly observed as white or yellow, unilateral nodules. They were approximately $1-2{\times}3-5mm$ in size. The tumors located in the region of iris and/or ciliary body invaded peripheral cornea. The microscopic features were usually composed of spindle cells arranged in parallel, forming gently curving bundles or whorls. The spindle cells had poorly defined cell boundaries, scant to moderate cytoplasm, fusiform nuclei and indistinct nucleoli. Mitotic figures were rare and areas of necrosis were present. The spindle cells had positive immunoreactivity for S-100 protein and vimentin but negative for desmin, collagen and HMB-45 antibody. In special histochemical studies, the spindle cells react with Gomori's stain for argyrophih fibers, Prussian blue stain for iron but negative with Masson-Fontana's stain for melanin granules. Ultrastructurally, cytoplasmic premelanosomes were not observed in the tumor cells due to the poor preservation of tumor masses. Based on the results, the tumors were diagnosed as amelanotic melanoma.