• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.465-468
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• 1997

A Study on Computer Assisted Diagnosis (CAD) system extract ing lung cancer part from Digital X-ray Computerized Tomography(CT) image is discussed in this paper. It is very crucial to segment the image of lung into the three organ area such as inside, outside and the hilum so that the variant image processing algorithm can be applied an each area respectively. In this paper, the efficient algorithm extracting lung cancer part is proposed with characterizing lung hilum part and its associated vessel patterns.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권4호
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• pp.595-617
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• 2010

This paper proposes a novel of a personalized Computer Assisted Language Learning (CALL) system based on learner's cognitive abilities related to foreign language proficiency. In this CALL system, a strategy of retrieval learning, a method of learning memory cycle, and a method of repeated learning are applied for effective vocabulary memorization. The system is designed to offer personalized learning based on cognitive abilities related to the human language process. For this, the proposed CALL system has a cognitive diagnosis module which can measure five types of cognitive abilities. The results of this diagnosis are used to create dynamic learning scenarios for personalized learning and to evaluate user performance in the learning. This system is also designed in order to have users be able to create learning word lists and to share them simply with various functions based on open APIs. Additionally, through experiments, it has shown that this system helps students to learn English vocabulary effectively and enhances their foreign language skills.

• Journal of Gastric Cancer
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• 제23권3호
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• pp.410-427
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• 2023

Recent advances in artificial intelligence (AI) have provided novel tools for rapid and precise pathologic diagnosis. The introduction of digital pathology has enabled the acquisition of scanned slide images that are essential for the application of AI. The application of AI for improved pathologic diagnosis includes the error-free detection of potentially negligible lesions, such as a minute focus of metastatic tumor cells in lymph nodes, the accurate diagnosis of potentially controversial histologic findings, such as very well-differentiated carcinomas mimicking normal epithelial tissues, and the pathological subtyping of the cancers. Additionally, the utilization of AI algorithms enables the precise decision of the score of immunohistochemical markers for targeted therapies, such as human epidermal growth factor receptor 2 and programmed death-ligand 1. Studies have revealed that AI assistance can reduce the discordance of interpretation between pathologists and more accurately predict clinical outcomes. Several approaches have been employed to develop novel biomarkers from histologic images using AI. Moreover, AI-assisted analysis of the cancer microenvironment showed that the distribution of tumor-infiltrating lymphocytes was related to the response to the immune checkpoint inhibitor therapy, emphasizing its value as a biomarker. As numerous studies have demonstrated the significance of AI-assisted interpretation and biomarker development, the AI-based approach will advance diagnostic pathology.

• Journal of information and communication convergence engineering
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• 제20권1호
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• pp.58-64
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• 2022

Breast ultrasonic reading is critical as a primary screening test for the early diagnosis of breast cancer. However, breast ultrasound examinations show significant differences in diagnosis based on the difference in image quality according to the ultrasonic equipment, experience, and proficiency of the examiner. Accordingly, studies are being actively conducted to analyze the texture characteristics of normal breast tissue, positive tumors, and malignant tumors using breast ultrasonography and to use them for computer-assisted diagnosis. In this study, breast ultrasonography was conducted to select 247 ultrasound images of 71 normal breast tissues, 87 fibroadenomas among benign tumors, and 89 malignant tumors. The selected images were calculated using a statistical method with 21 feature parameters extracted using the gray level co-occurrence matrix algorithm, and classified as normal breast tissue, benign tumor, and malignancy. In addition, we proposed five feature parameters that are available for computer-aided diagnosis of breast cancer classification. The average classification rate for normal breast tissue, benign tumors, and malignant tumors, using this feature parameter, was 82.8%.

• Animal Bioscience
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• 제34권8호
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• pp.1253-1270
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• 2021

Assessment of male fertility is based on the evaluation of sperm. Semen evaluation measures various sperm quality parameters as fertility indicators. However, semen evaluation has limitations, and it requires the advancement and application of strict quality control methods to interpret the results. This article reviews the recent advances in evaluating various sperm-specific quality characteristics and methodologies, with the help of different assays to assess sperm-fertility status. Sperm evaluation methods that include conventional microscopic methods, computer-assisted sperm analyzers (CASA), and flow cytometric analysis, provide precise information related to sperm morphology and function. Moreover, profiling fertility-related biomarkers in sperm or seminal plasma can be helpful in predicting fertility. Identification of different sperm proteins and diagnosis of DNA damage has positively contributed to the existing pool of knowledge about sperm physiology and molecular anomalies associated with different infertility issues in males. Advances in methods and sperm-specific evaluation has subsequently resulted in a better understanding of sperm biology that has improved the diagnosis and clinical management of male factor infertility. Accurate sperm evaluation is of paramount importance in the application of artificial insemination and assisted reproductive technology. However, no single test can precisely determine fertility; the selection of an appropriate test or a set of tests and parameters is required to accurately determine the fertility of specific animal species. Therefore, a need to further calibrate the CASA and advance the gene expression tests is recommended for faster and field-level applications.

• 컴퓨터교육학회논문지
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• 제13권1호
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• pp.37-44
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• 2010

최근 효율적인 외국어 학습 및 진단을 위해 외국어학습의 뇌공학적 접근이 활발하게 이루어지고 있다. 본 논문은 기존의 지필고사를 대체할 수 있는 뇌공학적 외국어 능숙도 진단 도구를 개발하는 것을 목표로 이를 위해 기존 언어심리학 과제에서 주로 사용되었던 테스트들을 기반으로 외국어 능숙도 진단을 위한 도구를 개발 하였다. 본 논문에서 제안한 도구들은 학습자의 기억능력, 이해능력, 산출능력을 5가지 테스트를 통하여 대뇌의 정보처리 양상을 간접적으로 측정한다.

• 대한방사선기술학회지:방사선기술과학
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• 제28권2호
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• pp.123-128
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• 2005

의료 방사선영상 정보에서 방사선사에게 숙련도와 능력을 토대로 진단 가치가 높은 영상을 얻고자 한다. 그래서 방사선영상학의 더욱더 향상된 지식과 더 많은 학습으로 인한 임상교육이 이루어지고, 각 방사선사의 교육수준을 고려하여 다양한 종류의 교육을 할 필요가 있다. 본 연구에서는 웹 환경에서 멀티미디어 저작도구를 사용한 임상 경추골절 방사선영상 컴퓨터 교육보조(Computer Assisted Instruction) 시스템을 구현하고자 한다. 컴퓨터 교육보조 시스템은 신규 방사선사의 교육프로그램으로써 방사선영상촬영실에서 수행되는 경추골절 방사선영상획득의 전반적인 업무내용을 교육하고자 한다. 제안한 CAI 시스템은 경추골절 환자의 방사선 촬영기술교본의 웹 정보화로 더욱더 신속하고 정확한 영상을 획득 할 수 있으며, 정확한 진단결정에 따른 환자 치료에 크게 도움이 되는 유용한 프로그램으로 기대된다.

• Imaging Science in Dentistry
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• 제42권4호
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• pp.225-229
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• 2012

Purpose: This study aimed to evaluate the trabecular bone changes after alveolar bone grafting in unilateral cleft lip and palate (UCLP) patients using a computer-aided diagnosis (CAD) system. Materials and Methods: The occlusal radiographs taken from 50 UCLP patients were surveyed retrospectively. The images were categorized as: 50 images in group 0 (before bone grafting), 33 images in group 1 (one month after bone grafting), 24 images in group 2 (2-4 months after bone grafting), 15 images in group 3 (5-7 months after bone grafting), and 21 images in group 4 (8 or more months after bone grafting). Each image was grouped as either "non-cleft side" or "cleft side". The CAD system was used five times for each side to calculate the pixel area based on the mathematical morphology. Significant differences were found using a Wilcoxon signed ranks test or paired samples t test. Results: The pixel area showed a significant difference between the "non-cleft side" and "cleft side" in group 0 ($404.27{\pm}103.72/117.73{\pm}92.25$; p=0.00), group 1 ($434.29{\pm}86.70/388.31{\pm}109.51$; p=0.01), and group 4 ($430.98{\pm}98.11/366.71{\pm}154.59$; p=0.02). No significant differences were found in group 2 ($423.57{\pm}98.12/383.47{\pm}135.88$; p=0.06) or group 3 ($433.02{\pm}116.07/384.16{\pm}146.55$; p=0.19). Conclusion: Based on the design of this study, alveolar bone grafting was similar to normal bone within 2-7 months postoperatively.

• Applied Microscopy
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• 제51권
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• pp.6.1-6.9
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• 2021

Histopathology is a well-established standard diagnosis employed for the majority of malignancies, including breast cancer. Nevertheless, despite training and standardization, it is considered operator-dependent and errors are still a concern. Fractal dimension analysis is a computational image processing technique that allows assessing the degree of complexity in patterns. We aimed here at providing a robust and easily attainable method for introducing computer-assisted techniques to histopathology laboratories. Slides from two databases were used: A) Breast Cancer Histopathological; and B) Grand Challenge on Breast Cancer Histology. Set A contained 2480 images from 24 patients with benign alterations, and 5429 images from 58 patients with breast cancer. Set B comprised 100 images of each type: normal tissue, benign alterations, in situ carcinoma, and invasive carcinoma. All images were analyzed with the FracLac algorithm in the ImageJ computational environment to yield the box count fractal dimension (Db) results. Images on set A on 40x magnification were statistically different (p = 0.0003), whereas images on 400x did not present differences in their means. On set B, the mean Db values presented promising statistical differences when comparing. Normal and/or benign images to in situ and/or invasive carcinoma (all p < 0.0001). Interestingly, there was no difference when comparing normal tissue to benign alterations. These data corroborate with previous work in which fractal analysis allowed differentiating malignancies. Computer-aided diagnosis algorithms may beneficiate from using Db data; specific Db cut-off values may yield ~ 99% specificity in diagnosing breast cancer. Furthermore, the fact that it allows assessing tissue complexity, this tool may be used to understand the progression of the histological alterations in cancer.

• 대한의용생체공학회:의공학회지
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• 제12권4호
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• pp.303-308
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• 1991

Computer assisted cardiac mapping system has made it possible to display local activation times of the heart using a simultaneous multi-point data aquisition system, and opened an era in electrophyslology guided cardiac arrhythmia surgery especially in ventricular tachycardia. In this study, we have developed a 64 channel computerized cardiacmapping system us:ng a micro-computer for basic reasearch of electrophysiology and electrical propagation in cardiac arrhythmias. The significant tasks of this study were the simultaneous acquisition of large amount of data from 64 sites, accurate and rapid analysis, and the effective display of the analyzed data. To solve these problems, we made a 64 channel signal pre-processing board in order to amplify and fitter the raw signals. And we developed the soflu'are Yor cardiac isochronous mapping whictl is presented immediately ama computer-generated graphics. This system is expected 4o enable us to study pathophyslology of cardiac arrhythmia and to improve the results of diagnosis and surgical treatments for cardiac arrhythmia.