{"scopus_import":1,"quality_controlled":"1","related_material":{"record":[{"relation":"later_version","status":"public","id":"1289"}]},"title":"The classification of endoscopy images with persistent homology","_id":"1568","author":[{"first_name":"Olga","full_name":"Dunaeva, Olga","last_name":"Dunaeva"},{"orcid":"0000-0002-9823-6833","first_name":"Herbert","full_name":"Edelsbrunner, Herbert","id":"3FB178DA-F248-11E8-B48F-1D18A9856A87","last_name":"Edelsbrunner"},{"first_name":"Anton","full_name":"Lukyanov, Anton","last_name":"Lukyanov"},{"first_name":"Michael","full_name":"Machin, Michael","last_name":"Machin"},{"last_name":"Malkova","full_name":"Malkova, Daria","first_name":"Daria"}],"doi":"10.1109/SYNASC.2014.81","conference":{"start_date":"2014-09-22","end_date":"2014-09-25","name":"SYNASC: Symbolic and Numeric Algorithms for Scientific Computing","location":"Timisoara, Romania"},"oa_version":"None","abstract":[{"text":"Aiming at the automatic diagnosis of tumors from narrow band imaging (NBI) magnifying endoscopy (ME) images of the stomach, we combine methods from image processing, computational topology, and machine learning to classify patterns into normal, tubular, vessel. Training the algorithm on a small number of images of each type, we achieve a high rate of correct classifications. The analysis of the learning algorithm reveals that a handful of geometric and topological features are responsible for the overwhelming majority of decisions.","lang":"eng"}],"publication":"Proceedings - 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","publication_status":"published","type":"conference","publist_id":"5603","date_updated":"2023-02-21T16:57:29Z","language":[{"iso":"eng"}],"day":"05","publisher":"IEEE","status":"public","year":"2015","page":"7034731","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","date_published":"2015-02-05T00:00:00Z","department":[{"_id":"HeEd"}],"acknowledgement":"This research is supported by the project No. 477 of P.G. Demidov Yaroslavl State University within State Assignment for Research.","month":"02","date_created":"2018-12-11T11:52:46Z","citation":{"ieee":"O. Dunaeva, H. Edelsbrunner, A. Lukyanov, M. Machin, and D. Malkova, “The classification of endoscopy images with persistent homology,” in <i>Proceedings - 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing</i>, Timisoara, Romania, 2015, p. 7034731.","mla":"Dunaeva, Olga, et al. “The Classification of Endoscopy Images with Persistent Homology.” <i>Proceedings - 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing</i>, IEEE, 2015, p. 7034731, doi:<a href=\"https://doi.org/10.1109/SYNASC.2014.81\">10.1109/SYNASC.2014.81</a>.","ama":"Dunaeva O, Edelsbrunner H, Lukyanov A, Machin M, Malkova D. The classification of endoscopy images with persistent homology. In: <i>Proceedings - 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing</i>. IEEE; 2015:7034731. doi:<a href=\"https://doi.org/10.1109/SYNASC.2014.81\">10.1109/SYNASC.2014.81</a>","short":"O. Dunaeva, H. Edelsbrunner, A. Lukyanov, M. Machin, D. Malkova, in:, Proceedings - 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, IEEE, 2015, p. 7034731.","apa":"Dunaeva, O., Edelsbrunner, H., Lukyanov, A., Machin, M., &#38; Malkova, D. (2015). The classification of endoscopy images with persistent homology. In <i>Proceedings - 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing</i> (p. 7034731). Timisoara, Romania: IEEE. <a href=\"https://doi.org/10.1109/SYNASC.2014.81\">https://doi.org/10.1109/SYNASC.2014.81</a>","ista":"Dunaeva O, Edelsbrunner H, Lukyanov A, Machin M, Malkova D. 2015. The classification of endoscopy images with persistent homology. Proceedings - 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing. SYNASC: Symbolic and Numeric Algorithms for Scientific Computing, 7034731.","chicago":"Dunaeva, Olga, Herbert Edelsbrunner, Anton Lukyanov, Michael Machin, and Daria Malkova. “The Classification of Endoscopy Images with Persistent Homology.” In <i>Proceedings - 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing</i>, 7034731. IEEE, 2015. <a href=\"https://doi.org/10.1109/SYNASC.2014.81\">https://doi.org/10.1109/SYNASC.2014.81</a>."}}