Focused Review Series: Application of Artificial Intelligence in GI Endoscopy
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Lesion-Based Convolutional Neural Network in Diagnosis of Early Gastric Cancer
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Hong Jin Yoon, Jie-Hyun Kim
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Clin Endosc 2020;53(2):127-131. Published online March 30, 2020
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DOI: https://doi.org/10.5946/ce.2020.046
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Abstract
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- Diagnosis and evaluation of early gastric cancer (EGC) using endoscopic images is significantly important; however, it has some limitations. In several studies, the application of convolutional neural network (CNN) greatly enhanced the effectiveness of endoscopy. To maximize clinical usefulness, it is important to determine the optimal method of applying CNN for each organ and disease. Lesion�-based CNN is a type of deep learning model designed to learn the entire lesion from endoscopic images. This review describes the application of lesion-based CNN technology in diagnosis of EGC.
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Focused Review Series: Optical Diagnosis and New Management Strategy of Colorectal Polyps
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Endoscopic Assessment of Colorectal Cancer with Superficial or Deep Submucosal Invasion Using Magnifying Colonoscopy
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Shinji Tanaka, Nana Hayashi, Shiro Oka, Kazuaki Chayama
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Clin Endosc 2013;46(2):138-146. Published online March 31, 2013
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DOI: https://doi.org/10.5946/ce.2013.46.2.138
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Abstract
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Among early colorectal carcinoma, endoscopic treatment is generally indicative for cases with intramucosal to submucosal (SM) superficial invasion, because cases with SM deep invasion should be treated surgically due to the risk of lymph node metastasis. It is important, therefore, to distinguish between superficial and deep SM invasion in early colorectal carcinoma prior to treatment. In this review we assessed the clinical usefulness and knack of pit pattern and narrow band imaging (NBI) diagnosis using magnifying observation. VN type pit pattern, type C3 in NBI Hiroshima classification and NBI type 3 in NBI international colorectal endoscopic (NICE) classification are useful predictors of SM deep invasion. In NBI magnifying observation evaluation of both the vascular pattern and surface pattern are important. We have to use pit pattern diagnosis and NBI magnifying diagnosis as the situation demands with the knowledge of both advantage and disadvantage in each diagnostic method.
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