• Clinical Endoscopy
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• 제51권6호
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• pp.527-533
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• 2018

There have been many advances in endoscopic imaging technologies. Magnifying endoscopy with narrow-band imaging is an innovative optical technology that enables the precise discrimination of structural changes on the mucosal surface. Several studies have demonstrated its usefulness and superiority for tumor detection and differential diagnosis in the stomach as compared with conventional endoscopy. Furthermore, magnifying endoscopy with narrow-band imaging has the potential to predict the invasion depth and tumor margins during gastric endoscopic submucosal dissection. Classifications of the findings of magnifying endoscopy with narrow-band imaging based on microvascular and pit patterns have been proposed and have shown excellent correlations with invasion depth confirmed by microscopy. In terms of tumor margin prediction, magnifying endoscopy with narrow-band imaging offers superior delineation of gastric tumor margins compared with traditional chromoendoscopy with indigo carmine. The limitations of narrow-band imaging, such as the need for considerable training, long procedure time, and lack of studies about its usefulness in undifferentiated cancer, should be resolved to confirm its value as a complementary method to endoscopic submucosal dissection. However, the role of magnifying endoscopy with narrow-band imaging is expected to increase steadily with the increasing use of endoscopic submucosal dissection for the treatment of gastric tumors.

• Journal of Digestive Cancer Research
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• 제10권2호
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• pp.56-64
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• 2022

Narrow-band imaging (NBI) is the most widely used image-enhanced endoscopic technique. The superficial microanatomy of gastric mucosa can be visualized when used with a magnifying endoscopy with narrow-band imaging (ME-NBI). The diagnostic criteria for early gastric cancer (EGC), using the classification system for microvascular and microsurface pattern of ME-NBI, have been developed, and their usefulness has been proven in the differential diagnosis of small depressed cancer from focal gastritis and in lateral extent delineation of EGC. Some studies reported on the prediction of histologic differentiation and invasion depth of gastric cancer using ME-NBI; however, its application is limited in clinical practice, and further well-designed studies are necessary. Clinicians should understand the ME-NBI classification system and acquire appropriate diagnostic skills through various experiences and training to improve the quality of endoscopy for EGC diagnosis.

• Clinical Endoscopy
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• 제55권1호
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• pp.113-121
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• 2022

Background/Aims: We have been developing artificial intelligence based polyp histology prediction (AIPHP) method to classify Narrow Band Imaging (NBI) magnifying colonoscopy images to predict the hyperplastic or neoplastic histology of polyps. Our aim was to analyze the accuracy of AIPHP and narrow-band imaging international colorectal endoscopic (NICE) classification based histology predictions and also to compare the results of the two methods. Methods: We studied 373 colorectal polyp samples taken by polypectomy from 279 patients. The documented NBI still images were analyzed by the AIPHP method and by the NICE classification parallel. The AIPHP software was created by machine learning method. The software measures five geometrical and color features on the endoscopic image. Results: The accuracy of AIPHP was 86.6% (323/373) in total of polyps. We compared the AIPHP accuracy results for diminutive and non-diminutive polyps (82.1% vs. 92.2%; p=0.0032). The accuracy of the hyperplastic histology prediction was significantly better by NICE compared to AIPHP method both in the diminutive polyps (n=207) (95.2% vs. 82.1%) (p<0.001) and also in all evaluated polyps (n=373) (97.1% vs. 86.6%) (p<0.001) Conclusions: Our artificial intelligence based polyp histology prediction software could predict histology with high accuracy only in the large size polyp subgroup.

• 천문학논총
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• 제15권spc1호
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• pp.39-60
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• 2000

We will discuss two-dimmensional spectrophotometry including long-slit spectroscopy and narrow-band imaging. The basic principles, applications, and techniques of observations and data reduction of spectroscopy and spectrophotometry for extended objects are described. This discussion will focus on practical long-slit spectroscopy using a Cassegrain spectrograph attached with 2 or 4m class telescopes and on imaging spectrophotometry using narrow-band interference filter sets. We will discuss scientific applications.

• Clinical Endoscopy
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• 제51권6호
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• pp.541-546
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• 2018

Recent advances in cholangiopancreatoscopy technology permit image-enhanced endoscopy (IEE) for pancreatobiliary diseases. There are limitations in endoscopy performance and in the study of the clinical role of IEE in bile duct or pancreatic duct diseases. However, currently available IEEs during cholangiopancreatoscopy including traditional dye-aided chromoendoscopy, autofluorescence imaging, narrow-band imaging, and i-Scan have been evaluated and reported previously. Although the clinical role of IEE in pancreatobiliary diseases should be verified in future studies, IEE is a useful promising tool in the evaluation of bile duct or pancreatic duct mucosal lesions.

• 천문학회보
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• 제43권1호
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• pp.49.2-49.2
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• 2018

Flux calibration for narrow band photometric data gives us an opportunity to get a line flux of extended targets. We developed flux calibration processes for narrow band photometry using broad band filters as a continuum indicator. We derived parameters for color correction and zero point correction including color terms. Applying our method, we successfully subtracted continuum emissions and calibrated the emission lines from an FU Ori type object, V960 Mon.

• Clinical Endoscopy
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• 제56권4호
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• pp.455-456
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• 2023

• Clinical Endoscopy
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• 제57권1호
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• pp.11-17
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• 2024

Although magnifying endoscopy with narrow-band imaging is the standard diagnostic test for gastric cancer, diagnosing gastric cancer using this technology requires considerable skill. Artificial intelligence has superior image recognition, and its usefulness in endoscopic image diagnosis has been reported in many cases. The diagnostic performance (accuracy, sensitivity, and specificity) of artificial intelligence using magnifying endoscopy with narrow band still images and videos for gastric cancer was higher than that of expert endoscopists, suggesting the usefulness of artificial intelligence in diagnosing gastric cancer. Histological diagnosis of gastric cancer using artificial intelligence is also promising. However, previous studies on the use of artificial intelligence to diagnose gastric cancer were small-scale; thus, large-scale studies are necessary to examine whether a high diagnostic performance can be achieved. In addition, the diagnosis of gastric cancer using artificial intelligence has not yet become widespread in clinical practice, and further research is necessary. Therefore, in the future, artificial intelligence must be further developed as an instrument, and its diagnostic performance is expected to improve with the accumulation of numerous cases nationwide.

• Clinical Endoscopy
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• 제56권5호
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• pp.553-562
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• 2023

Colonoscopy plays an important role in reducing the incidence and mortality of colorectal cancer by detecting adenomas and other precancerous lesions. Image-enhanced endoscopy (IEE) increases lesion visibility by enhancing the microstructure, blood vessels, and mucosal surface color, resulting in the detection of colorectal lesions. In recent years, various IEE techniques have been used in clinical practice, each with its unique characteristics. Numerous studies have reported the effectiveness of IEE in the detection of colorectal lesions. IEEs can be divided into two broad categories according to the nature of the image: images constructed using narrow-band wavelength light, such as narrow-band imaging and blue laser imaging/blue light imaging, or color images based on white light, such as linked color imaging, texture and color enhancement imaging, and i-scan. Conversely, artificial intelligence (AI) systems, such as computer-aided diagnosis systems, have recently been developed to assist endoscopists in detecting colorectal lesions during colonoscopy. To gain a better understanding of the features of each IEE, this review presents the effectiveness of each type of IEE and their combination with AI for colorectal lesion detection by referencing the latest research data.

• Tuberculosis and Respiratory Diseases
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• 제68권1호
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• pp.16-21
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• 2010

Background: Lung cancer is usually diagnosed at an advanced stage, resulting in a poor prognosis. The detection of these lesions at an earlier stage would be a clear benefit to patients. However, it is extremely difficult to detect carcinomatous lesions in the bronchial mucosal sites during a routine bronchoscopy. Methods: This study employed a novel optical technique, known as narrowband imaging (NBI), which allows noninvasive visualization of the microvascular structure of an organ's surface using reflected light. Results: Narrow band imaging was performed on 10 patients who were radiologically suspicious or had a high risk of lung cancer. The median age of the patients was 57.5 years (range, 44~81 years), and 80% of the patients were male. All lesions showed a microvascular proliferation pattern (dotted, tortuous and abruptly ending vessel) on the magnified NBI. Two lesions were confirmed histologically to be adenocarcinoma and the remaining lesions were squamous cell carcinomas. Two lesions were confirmed histologically to be a carcinoma in situ. Conclusion: NBI is a promising and potentially powerful tool for identifying carcinomas at an earlier stage or a central lesion during a routine bronchoscopy examination.