{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T17:40:12Z","timestamp":1756489212804,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":13,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,24]],"date-time":"2024-05-24T00:00:00Z","timestamp":1716508800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Shandong First Medical University and Shandong Academy of Medical Sciences","award":["S202310439161"],"award-info":[{"award-number":["S202310439161"]}]},{"name":"Shandong Province Undergraduate Teaching Reform Research Project","award":["Z2022141"],"award-info":[{"award-number":["Z2022141"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,5,24]]},"DOI":"10.1145\/3674029.3674057","type":"proceedings-article","created":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T12:25:22Z","timestamp":1726057522000},"page":"170-174","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Lung Nodule Detection Using K-Means Segmentation and V-Net"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-2651-0979","authenticated-orcid":false,"given":"Qi","family":"Xin","sequence":"first","affiliation":[{"name":"Shandong First Medical University and Shandong Academy of Medical Sciences, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2791-0966","authenticated-orcid":false,"given":"Lei","family":"Peng","sequence":"additional","affiliation":[{"name":"Shandong First Medical University and Shandong Academy of Medical Sciences, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3895-1170","authenticated-orcid":false,"given":"Lanhua","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shandong First Medical University and Shandong Academy of Medical Sciences, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0517-472X","authenticated-orcid":false,"given":"Xiuyun","family":"Yang","sequence":"additional","affiliation":[{"name":"Shandong First Medical University and Shandong Academy of Medical Sciences, China"}]}],"member":"320","published-online":{"date-parts":[[2024,9,11]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21338"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1911793"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2536809"},{"key":"e_1_3_2_1_4_1","unstructured":"MacQueen J. 1967. Some methods for classification and analysis of multivariate observations."},{"volume-title":"Medical Image Segmentation Using K-Means Clustering and Improved Watershed Algorithm. in 2006 IEEE Southwest Symposium on Image Analysis and Interpretation. 61-65","author":"Ng H.P.","key":"e_1_3_2_1_5_1","unstructured":"Ng H.P., Ong S.H., Foong K.W.C., Goh P.S. and Nowinski W.L. 2006. Medical Image Segmentation Using K-Means Clustering and Improved Watershed Algorithm. in 2006 IEEE Southwest Symposium on Image Analysis and Interpretation. 61-65."},{"volume-title":"2017 4th International Conference on Advances in Electrical Engineering (ICAEE). 731-736","author":"Sarker P.","key":"e_1_3_2_1_6_1","unstructured":"Sarker P., Shuvo M.M.H., Hossain Z. and Hasan S. 2017. Segmentation and classification of lung tumor from 3D CT image using K-means clustering algorithm. in 2017 4th International Conference on Advances in Electrical Engineering (ICAEE). 731-736."},{"volume-title":"2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). 2302-2308","author":"Afshar P.","key":"e_1_3_2_1_7_1","unstructured":"Afshar P., Ahmadi A. and Zarandi M.H.F. 2016. Lung tumor area recognition in CT images based on Gustafson-Kessel clustering. in 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). 2302-2308."},{"volume-title":"V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation. in 2016 Fourth International Conference on 3D Vision (3DV). 565-571","author":"Milletari F.","key":"e_1_3_2_1_8_1","unstructured":"Milletari F., Navab N. and Ahmadi S.A. 2016. V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation. in 2016 Fourth International Conference on 3D Vision (3DV). 565-571."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12880-021-00728-8"},{"volume-title":"2015 IEEE International Conference on Computer Vision (ICCV). 1026-1034","author":"He K.","key":"e_1_3_2_1_10_1","unstructured":"He K., Zhang X., Ren S. and Sun J. 2015. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification. in 2015 IEEE International Conference on Computer Vision (ICCV). 1026-1034."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3026658"},{"volume-title":"Proceedings of the IEEE international conference on computer vision. 4489-4497","author":"Tran D.","key":"e_1_3_2_1_12_1","unstructured":"Tran D., Bourdev L., Fergus R., Torresani L. and Paluri M. 2015. Learning spatiotemporal features with 3d convolutional networks. in Proceedings of the IEEE international conference on computer vision. 4489-4497."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.10.013"}],"event":{"name":"ICMLT 2024: 2024 9th International Conference on Machine Learning Technologies","acronym":"ICMLT 2024","location":"Oslo Norway"},"container-title":["2024 9th International Conference on Machine Learning Technologies (ICMLT)"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3674029.3674057","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3674029.3674057","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T17:04:02Z","timestamp":1756487042000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3674029.3674057"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,24]]},"references-count":13,"alternative-id":["10.1145\/3674029.3674057","10.1145\/3674029"],"URL":"https:\/\/doi.org\/10.1145\/3674029.3674057","relation":{},"subject":[],"published":{"date-parts":[[2024,5,24]]},"assertion":[{"value":"2024-09-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}