{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T10:59:27Z","timestamp":1768820367826,"version":"3.49.0"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,8,5]],"date-time":"2024-08-05T00:00:00Z","timestamp":1722816000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,8,5]],"date-time":"2024-08-05T00:00:00Z","timestamp":1722816000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100013173","name":"Gyeonggi-do Regional Research Center","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013173","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003052","name":"Ministry of Trade, Industry and Energy","doi-asserted-by":"publisher","award":["K_G012001187801"],"award-info":[{"award-number":["K_G012001187801"]}],"id":[{"id":"10.13039\/501100003052","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Digit Imaging. Inform. med."],"DOI":"10.1007\/s10278-024-01208-5","type":"journal-article","created":{"date-parts":[[2024,8,5]],"date-time":"2024-08-05T16:55:42Z","timestamp":1722876942000},"page":"281-290","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Airway and Airway Obstruction Site Segmentation Study Using U-Net with Drug-Induced Sleep Endoscopy Images"],"prefix":"10.1007","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-5596-4607","authenticated-orcid":false,"given":"Yeong Hun","family":"Kang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2687-6919","authenticated-orcid":false,"given":"Jin Youp","family":"Kim","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0443-0051","authenticated-orcid":false,"given":"Young Jae","family":"Kim","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2926-2146","authenticated-orcid":false,"given":"Sung Hyun","family":"Kim","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9714-6038","authenticated-orcid":false,"given":"Kwang Gi","family":"Kim","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1361-8585","authenticated-orcid":false,"given":"Chae-Seo","family":"Rhee","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,8,5]]},"reference":[{"key":"1208_CR1","doi-asserted-by":"crossref","unstructured":"HONG, Sung-Lyong, et al. Sleep Endoscopy in Korean Males with Obstructive Sleep Apnea. Journal of Clinical Otolaryngology Head and Neck Surgery, 2012, 23.2: 224\u2013229.","DOI":"10.35420\/jcohns.2012.23.2.224"},{"key":"1208_CR2","doi-asserted-by":"crossref","unstructured":"YOON, Dae Wui; KIM, Jin Kwan; SHIN, Chol. Epidemiology and etiology of obstructive sleep apnea. The Korean Journal of Medicine, 2015, 89.1: 6\u201312.","DOI":"10.3904\/kjm.2015.89.1.6"},{"key":"1208_CR3","doi-asserted-by":"crossref","unstructured":"Jun, Beom-Cho et al. Dynamic evaluation of the velopharynx in sleep-disordered breathing patients using video endoscopy. J Clin Otolaryngol Head Neck Surg, 2003, 14:288\u2013293.","DOI":"10.35420\/jcohns.2003.14.2.288"},{"key":"1208_CR4","doi-asserted-by":"crossref","unstructured":"KIM, Sung Wan. Skeletal surgery in obstructive sleep apnea. Hanyang Medical Reviews, 2013, 33.4: 233\u2013238.","DOI":"10.7599\/hmr.2013.33.4.233"},{"key":"1208_CR5","doi-asserted-by":"crossref","unstructured":"LEE, Young Chul; LEE, Ki Young; CHOI, Sung Chul. Airway Obstrauction during Endotracheal Anestheaia-Case report. Korean Journal of Anesthesiology, 1987, 20.3: 432\u2013434.","DOI":"10.4097\/kjae.1987.20.3.432"},{"key":"1208_CR6","doi-asserted-by":"crossref","unstructured":"KIM, Chi-Hong, et al. The effect of nasal CPAP in obstructive sleep apnea syndrome. Tuberculosis and Respiratory Diseases, 1993, 40.5: 501\u2013508.","DOI":"10.4046\/trd.1993.40.5.501"},{"key":"1208_CR7","doi-asserted-by":"crossref","unstructured":"CHOI, Jang Won, et al. Analysis of correlation between results of polysomnography and obstructive structure by drug-induced sleep endoscopy in obstructive sleep apnea patients. Korean J Otorhinolaryngol-Head Neck Surg, 2013, 56.6: 346\u201353.","DOI":"10.3342\/kjorl-hns.2013.56.6.346"},{"key":"1208_CR8","doi-asserted-by":"crossref","unstructured":"MEHTA, Vedant. Towards Real-Time Polyp Segmentation During Colonoscopy Using an EfficientNet-Based UNet Architecture. In: 2023 IEEE 23rd International Conference on Bioinformatics and Bioengineering (BIBE). IEEE Computer Society, 2023. p. 447\u2013451.","DOI":"10.1109\/BIBE60311.2023.00079"},{"key":"1208_CR9","doi-asserted-by":"crossref","unstructured":"GHOSH, Tonmoy; LI, Linfeng; CHAKARESKI, Jacob. Effective deep learning for semantic segmentation based bleeding zone detection in capsule endoscopy images. In: 2018 25th IEEE International Conference on Image Processing (ICIP). IEEE, 2018. p. 3034\u20133038.","DOI":"10.1109\/ICIP.2018.8451300"},{"key":"1208_CR10","doi-asserted-by":"crossref","unstructured":"ZHAO, Yu, et al. A Study on Intrarenal Porous Segmentation of Endoscopic Images. In: 2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM). IEEE, 2021. p. 516\u2013521.","DOI":"10.1109\/ICARM52023.2021.9536211"},{"key":"1208_CR11","doi-asserted-by":"crossref","unstructured":"DO, Hong-Quan, et al. Evaluation of U-Net and Its Variants in Solving Upper Gastrointestinal Endoscopy Segmentation. In: 2021 15th International Conference on Advanced Computing and Applications (ACOMP). IEEE, 2021. p. 70\u201377.","DOI":"10.1109\/ACOMP53746.2021.00016"},{"key":"1208_CR12","doi-asserted-by":"crossref","unstructured":"HAMAD, Ali, et al. Automated segmentation of the vocal folds in laryngeal endoscopy videos using deep convolutional regression networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops. 2019. p. 0\u20130.","DOI":"10.1109\/CVPRW.2019.00023"},{"key":"1208_CR13","doi-asserted-by":"crossref","unstructured":"CHEN, Chun-Ting, et al. Deep learning for identification of velopharyngeal patency in drug-induced sleep endoscopy. In: 2023 12th International Conference on Awareness Science and Technology (iCAST). IEEE, 2023. p. 151\u2013155.","DOI":"10.1109\/iCAST57874.2023.10359292"},{"key":"1208_CR14","first-page":"7201","volume":"2019","author":"POORNESHWARAN, J. M., Polyp segment","year":"2019","unstructured":"POORNESHWARAN, J. M., et al. Polyp segmentation using generative adversarial network. In: 2019 41St annual international conference of the IEEE engineering in medicine and biology society (EMBC). IEEE, 2019. p. 7201\u20137204.","journal-title":"IEEE"},{"key":"1208_CR15","doi-asserted-by":"crossref","unstructured":"HOSSAIN, Md Shakhawat, et al. Deeppoly: deep learning based polyps segmentation and classification for autonomous colonoscopy examination. IEEE Access, 2023.","DOI":"10.1109\/ACCESS.2023.3310541"},{"key":"1208_CR16","doi-asserted-by":"crossref","unstructured":"LI, Xinyi, et al. Multi-task refined boundary-supervision U-Net (MRBSU-Net) for gastrointestinal stromal tumor segmentation in endoscopic ultrasound (EUS) images. IEEE Access, 2020, 8: 5805\u20135816.","DOI":"10.1109\/ACCESS.2019.2963472"},{"key":"1208_CR17","doi-asserted-by":"crossref","unstructured":"KIM, Taewan, et al. Development of ResNet152 UNet++-based segmentation algorithm for the tympanic membrane and affected areas. IEEE Access, 2023.","DOI":"10.1109\/ACCESS.2023.3281693"},{"key":"1208_CR18","doi-asserted-by":"crossref","unstructured":"ABIDIN, Nadzurah Zainal; ISMAIL, Amelia Ritahani. Federated deep learning for automated detection of diabetic retinopathy. In: 2022 IEEE 8th International Conference on Computing, Engineering and Design (ICCED). IEEE, 2022. p. 1\u20135.","DOI":"10.1109\/ICCED56140.2022.10010636"},{"key":"1208_CR19","doi-asserted-by":"crossref","unstructured":"KHUDHAIR, Zaid Nidhal, et al. Color to grayscale image conversion based on singular value decomposition. Ieee Access, 2023, 11: 54629\u201354638.","DOI":"10.1109\/ACCESS.2023.3279734"},{"key":"1208_CR20","doi-asserted-by":"crossref","unstructured":"RAHMAN, Mohammed Ehsan Ur, et al. A Quantitative Analysis of Basic vs. Deep Learning-based Image Data Augmentation Techniques. In: 2021 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES). IEEE, 2021. p. 1\u20139.","DOI":"10.1109\/ICSES52305.2021.9633781"},{"key":"1208_CR21","doi-asserted-by":"crossref","unstructured":"CHLAP, Phillip, et al. A review of medical image data augmentation techniques for deep learning applications. Journal of Medical Imaging and Radiation Oncology, 2021, 65.5: 545\u2013563.","DOI":"10.1111\/1754-9485.13261"},{"issue":"3","key":"1208_CR22","doi-asserted-by":"publisher","first-page":"440","DOI":"10.5370\/KIEE.2023.72.3.440","volume":"72","author":"Tae-Hoon Kim","year":"2023","unstructured":"Kim, Tae-Hoon; Park, Jong-Jin. Teeth Segmentation for Orthodontics based on Deep Learning. The Transactions of the Korean Institute of Electrical Engineers, 2023, 72(3): 440\u2013446.","journal-title":"The Transactions of the Korean Institute of Electrical Engineers"},{"key":"1208_CR23","doi-asserted-by":"crossref","unstructured":"RONNEBERGER, Olaf; FISCHER, Philipp; BROX, Thomas. U-net: Convolutional networks for biomedical image segmentation. In: Medical image computing and computer-assisted intervention\u2013MICCAI 2015: 18th international conference, Munich, Germany, October 5\u20139, 2015, proceedings, part III 18. Springer International Publishing, 2015. p. 234\u2013241.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"1208_CR24","doi-asserted-by":"crossref","unstructured":"JAHNAVI, T.; VASUNDHARA, D. N. Segmentation of medical images using U-Net++. In: 2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N). IEEE, 2022. p. 801\u2013807.","DOI":"10.1109\/ICAC3N56670.2022.10074438"},{"key":"1208_CR25","doi-asserted-by":"crossref","unstructured":"MIRZARGAR, Mahsa; WHITAKER, Ross T.; KIRBY, Robert M. Curve boxplot: Generalization of boxplot for ensembles of curves. IEEE transactions on visualization and computer graphics, 2014, 20.12: 2654\u20132663.","DOI":"10.1109\/TVCG.2014.2346455"}],"container-title":["Journal of Imaging Informatics in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-024-01208-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10278-024-01208-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-024-01208-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,10]],"date-time":"2025-02-10T19:31:05Z","timestamp":1739215865000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10278-024-01208-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,5]]},"references-count":25,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,2]]}},"alternative-id":["1208"],"URL":"https:\/\/doi.org\/10.1007\/s10278-024-01208-5","relation":{},"ISSN":["2948-2933"],"issn-type":[{"value":"2948-2933","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,5]]},"assertion":[{"value":"29 April 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 July 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 July 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 August 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This retrospective study was approved by the Institutional Review Board of Seoul National University Hospital (IRB No. H-2305-015-1428).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}},{"value":"The requirement for informed consent was waived due to the retrospective nature of the study.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to Participate"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for Publication"}},{"value":"The authors declare no competing interests.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interests"}}]}}