{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:09:32Z","timestamp":1750219772692,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":30,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,7,14]],"date-time":"2023-07-14T00:00:00Z","timestamp":1689292800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,7,14]]},"DOI":"10.1145\/3614008.3614030","type":"proceedings-article","created":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T18:19:52Z","timestamp":1697566792000},"page":"150-155","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Research on Cervical Vertebrae Segmentation Based on Improved UNet Network"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-0107-3797","authenticated-orcid":false,"given":"Ruidong","family":"Tian","sequence":"first","affiliation":[{"name":"Taiyuan University of Science and Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4997-5568","authenticated-orcid":false,"given":"Qiusheng","family":"He","sequence":"additional","affiliation":[{"name":"Taiyuan University of Science and Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-3862-2386","authenticated-orcid":false,"given":"Hao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Taiyuan University of Science and Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,10,17]]},"reference":[{"key":"#cr-split#-e_1_3_2_1_1_1.1","doi-asserted-by":"crossref","unstructured":"S.M.Masudur Rahman Al Arif Karen Knapp and Greg Slabaugh.2018.Fully automatic cervical vertebrae segmentation framework for X-ray images.\u00a0Computer Methods & Programs in Biomedicine.157(May 2018) 95-111.https:\/\/doi.org\/10.1016\/j.cmpb.2018.01.006. 10.1016\/j.cmpb.2018.01.006","DOI":"10.1016\/j.cmpb.2018.01.006"},{"key":"#cr-split#-e_1_3_2_1_1_1.2","doi-asserted-by":"crossref","unstructured":"S.M.Masudur Rahman Al Arif Karen Knapp and Greg Slabaugh.2018.Fully automatic cervical vertebrae segmentation framework for X-ray images.\u00a0Computer Methods & Programs in Biomedicine.157(May 2018) 95-111.https:\/\/doi.org\/10.1016\/j.cmpb.2018.01.006.","DOI":"10.1016\/j.cmpb.2018.01.006"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1097\/01.ta.0000196673.58429.2a"},{"key":"#cr-split#-e_1_3_2_1_3_1.1","unstructured":"Zhu Yi-feng Zhao Kai Guo Li .2021.Automatic segmentation of cervical spine structures on MRI images based on deep learning :a preliminary study. Radiol Practice.36 12(December 2021) 1558-1562. https:\/\/doi.org\/10.13609\/j.cnki.1000-0313.2021.12.019. 10.13609\/j.cnki.1000-0313.2021.12.019"},{"key":"#cr-split#-e_1_3_2_1_3_1.2","unstructured":"Zhu Yi-feng Zhao Kai Guo Li .2021.Automatic segmentation of cervical spine structures on MRI images based on deep learning :a preliminary study. Radiol Practice.36 12(December 2021) 1558-1562. https:\/\/doi.org\/10.13609\/j.cnki.1000-0313.2021.12.019."},{"key":"e_1_3_2_1_4_1","article-title":"Place Perception for Robot Indoor Semantic Mapping:A Survey","volume":"43","author":"Bo Zhu","year":"2017","unstructured":"Zhu Bo , Gao Xiang , Zhao Yan-Nan . 2017 . Place Perception for Robot Indoor Semantic Mapping:A Survey . Acta Automatica Sinica. 43 ,4( April 2017 ),493-508. https:\/\/doi.org\/10.16383\/j.aas.2017.c160350. 10.16383\/j.aas.2017.c160350 Zhu Bo,Gao Xiang,Zhao Yan-Nan.2017.Place Perception for Robot Indoor Semantic Mapping:A Survey. Acta Automatica Sinica. 43,4(April 2017 ),493-508. https:\/\/doi.org\/10.16383\/j.aas.2017.c160350.","journal-title":"Acta Automatica Sinica."},{"key":"e_1_3_2_1_5_1","volume-title":"Image segmentation techniques.International .Journal of Future Computer and Communication\u00a03,2 (April","author":"Khan Muhammad Waseem","year":"2014","unstructured":"Muhammad Waseem Khan . 2014. A survey : Image segmentation techniques.International .Journal of Future Computer and Communication\u00a03,2 (April 2014 ),89. https:\/\/doi.org\/10.7763\/IJFCC.2014.V3.274. 10.7763\/IJFCC.2014.V3.274 Muhammad Waseem Khan. 2014.A survey: Image segmentation techniques.International .Journal of Future Computer and Communication\u00a03,2 (April 2014),89. https:\/\/doi.org\/10.7763\/IJFCC.2014.V3.274."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.05.004"},{"key":"e_1_3_2_1_7_1","volume-title":"Unet-Based Model of Alzheimer's Disease Lesion Segmentation.Computer Science and Application.12,1(January","author":"Chao Xu","year":"2022","unstructured":"Xu Chao , Wang Zhuowei , Liu Xiaodong .2022. Unet-Based Model of Alzheimer's Disease Lesion Segmentation.Computer Science and Application.12,1(January 2022 ),178-186.https:\/\/doi.org\/ 10.12677\/csa.2022.121019. 10.12677\/csa.2022.121019 Xu Chao,Wang Zhuowei,Liu Xiaodong.2022. Unet-Based Model of Alzheimer's Disease Lesion Segmentation.Computer Science and Application.12,1(January 2022),178-186.https:\/\/doi.org\/ 10.12677\/csa.2022.121019."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","unstructured":"Chen Lili Lin Jiuxiang Xu Tianmin Long Xiaosi.\u00a02009.The longitudinal sagittal growth changes of maxilla and mandible according to quantitative cervical vertebral maturation.\u00a0Journal of Huazhong University of Science and Technology [Medical Sciences]\u00a0.29 251-256. https:\/\/doi.org\/10.1007\/s11596-009-0224-z.    10.1007\/s11596-009-0224-z\nChen Lili Lin Jiuxiang Xu Tianmin Long Xiaosi.\u00a02009.The longitudinal sagittal growth changes of maxilla and mandible according to quantitative cervical vertebral maturation.\u00a0Journal of Huazhong University of Science and Technology [Medical Sciences]\u00a0.29 251-256. https:\/\/doi.org\/10.1007\/s11596-009-0224-z.","DOI":"10.1007\/s11596-009-0224-z"},{"key":"#cr-split#-e_1_3_2_1_9_1.1","doi-asserted-by":"crossref","unstructured":"Zhang Lei Wang Huan.2020.A novel segmentation method for cervical vertebrae based on PointNet++ and converge segmentation.Computer Methods and Programs in Biomedicine.200(October 2020) 105798. https:\/\/doi.org\/10.1016\/j.cmpb.2020.105798. 10.1016\/j.cmpb.2020.105798","DOI":"10.1016\/j.cmpb.2020.105798"},{"key":"#cr-split#-e_1_3_2_1_9_1.2","doi-asserted-by":"crossref","unstructured":"Zhang Lei Wang Huan.2020.A novel segmentation method for cervical vertebrae based on PointNet++ and converge segmentation.Computer Methods and Programs in Biomedicine.200(October 2020) 105798. https:\/\/doi.org\/10.1016\/j.cmpb.2020.105798.","DOI":"10.1016\/j.cmpb.2020.105798"},{"key":"e_1_3_2_1_10_1","volume-title":"a volumetric object recognition approach based on bivariate histograms of oriented gradients for vertebra detection in cervical spine MRI. Medical physics.41,8(August","author":"Daenzer Stefan","year":"2014","unstructured":"Stefan Daenzer , Stefan Freitag , Sandra von Sachsen , Hanno Steinke , Mathias Groll , J\u00fcrgen Meixensberger , Mario Leimert . 2014.VolHOG : a volumetric object recognition approach based on bivariate histograms of oriented gradients for vertebra detection in cervical spine MRI. Medical physics.41,8(August 2014 ),082305. https:\/\/doi.org\/10.1118\/1.4890587. 10.1118\/1.4890587 Stefan Daenzer, Stefan Freitag, Sandra von Sachsen, Hanno Steinke, Mathias Groll, J\u00fcrgen Meixensberger, Mario Leimert. 2014.VolHOG: a volumetric object recognition approach based on bivariate histograms of oriented gradients for vertebra detection in cervical spine MRI. Medical physics.41,8(August 2014),082305. https:\/\/doi.org\/10.1118\/1.4890587."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"crossref","unstructured":"Huang Juying. Jian Fengzeng Wu Hao and Li Haiyun. 2013. An improved level set method for vertebra CT image segmentation.\u00a0Biomedical engineering online.12 1 1-16.http:\/\/www.biomedical-engineering-online.com\/content\/12\/1\/48.  Huang Juying. Jian Fengzeng Wu Hao and Li Haiyun. 2013. An improved level set method for vertebra CT image segmentation.\u00a0Biomedical engineering online.12 1 1-16.http:\/\/www.biomedical-engineering-online.com\/content\/12\/1\/48.","DOI":"10.1186\/1475-925X-12-48"},{"key":"e_1_3_2_1_12_1","unstructured":"Liu Xia Gan Quan Li Bing Liu Xiao Wang Bo.2020.Automatic 3D vertebrae CT image active contour segmentation method based on weighted random forest.Opto-Electronic Engineering.47 12 200002.https:\/\/doi.org\/10.12086\/oee.2020.200002.    10.12086\/oee.2020.200002\nLiu Xia Gan Quan Li Bing Liu Xiao Wang Bo.2020.Automatic 3D vertebrae CT image active contour segmentation method based on weighted random forest.Opto-Electronic Engineering.47 12 200002.https:\/\/doi.org\/10.12086\/oee.2020.200002."},{"key":"#cr-split#-e_1_3_2_1_13_1.1","doi-asserted-by":"crossref","unstructured":"Szu-Hao Huang Yi-Hong Chu Shang-Hong Lai Carol L. Novak.2009.Learning-based vertebra detection and iterative normalized-cut segmentation for spinal MRI.\u00a0IEEE transactions on medical imaging.28 10 (May 2009) 1595-1605. https:\/\/doi.org\/10.1109\/TMI.2009.2023362. 10.1109\/TMI.2009.2023362","DOI":"10.1109\/TMI.2009.2023362"},{"key":"#cr-split#-e_1_3_2_1_13_1.2","doi-asserted-by":"crossref","unstructured":"Szu-Hao Huang Yi-Hong Chu Shang-Hong Lai Carol L. Novak.2009.Learning-based vertebra detection and iterative normalized-cut segmentation for spinal MRI.\u00a0IEEE transactions on medical imaging.28 10 (May 2009) 1595-1605. https:\/\/doi.org\/10.1109\/TMI.2009.2023362.","DOI":"10.1109\/TMI.2009.2023362"},{"key":"#cr-split#-e_1_3_2_1_14_1.1","unstructured":"Sun Wen-Yan Dong En-Qing Cao Zhu-Lou Zheng Qiang.2017.A robust local segmentation method based on fuzzy-energy based active contour.Acta Automatica Sinica.43 4(April 2017) 611-621. https:\/\/doi.org\/10.16383\/j.aas.2017.c160260. 10.16383\/j.aas.2017.c160260"},{"key":"#cr-split#-e_1_3_2_1_14_1.2","unstructured":"Sun Wen-Yan Dong En-Qing Cao Zhu-Lou Zheng Qiang.2017.A robust local segmentation method based on fuzzy-energy based active contour.Acta Automatica Sinica.43 4(April 2017) 611-621. https:\/\/doi.org\/10.16383\/j.aas.2017.c160260."},{"key":"e_1_3_2_1_15_1","first-page":"7298965","article-title":"Fully convolutional networks for semantic segmentation.In\u00a0Proceedings of the IEEE conference on computer vision and pattern recognition.IEEE,Boston","volume":"2015","author":"Jonathan Long","year":"2015","unstructured":"Long Jonathan , Shelhamer Evan , Darrell Trevor . 2015 . Fully convolutional networks for semantic segmentation.In\u00a0Proceedings of the IEEE conference on computer vision and pattern recognition.IEEE,Boston , USA,3431-3440.https:\/\/doi.org\/10.1109\/CVPR. 2015 . 7298965 . 10.1109\/CVPR Long Jonathan, Shelhamer Evan, Darrell Trevor.2015.Fully convolutional networks for semantic segmentation.In\u00a0Proceedings of the IEEE conference on computer vision and pattern recognition.IEEE,Boston, USA,3431-3440.https:\/\/doi.org\/10.1109\/CVPR. 2015.7298965.","journal-title":"USA,3431-3440.https:\/\/doi.org\/10.1109\/CVPR."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"crossref","unstructured":"Sun Ke Xiao Bin Liu Dong Wang Jangdong.2019.Deep high-resolution representation learning for human pose estimation.In\u00a0Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition.IEEE Long Beach 5693-5703.https:\/\/org\/10.1109\/CVPR.2019.00584.  Sun Ke Xiao Bin Liu Dong Wang Jangdong.2019.Deep high-resolution representation learning for human pose estimation.In\u00a0Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition.IEEE Long Beach 5693-5703.https:\/\/org\/10.1109\/CVPR.2019.00584.","DOI":"10.1109\/CVPR.2019.00584"},{"volume-title":"convolutional networks for biomedical image segmentation.In Proceedings of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention","author":"Olaf Ronneberger","key":"e_1_3_2_1_17_1","unstructured":"Ronneberger Olaf , Fischer Philipp , Brox Thomas .2015.U-Net : convolutional networks for biomedical image segmentation.In Proceedings of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention . Springer , Munich, Germany ,234\u2013241. https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28. 10.1007\/978-3-319-24574-4_28 Ronneberger Olaf, Fischer Philipp,Brox Thomas.2015.U-Net: convolutional networks for biomedical image segmentation.In Proceedings of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention.Springer, Munich, Germany ,234\u2013241. https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28."},{"key":"e_1_3_2_1_18_1","first-page":"770","article-title":"Deep residual learning for image recognition.In Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition ( CVPR ). IEEE","author":"Kaiming He","year":"2016","unstructured":"He Kaiming , Zhang Xiangyu , Ren Shaoqing , Sun Jian . 2016 . Deep residual learning for image recognition.In Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition ( CVPR ). IEEE , Las Vegas, USA , 770 - 778 . https:\/\/doi.org\/10.1109\/CVPR. 2016. 90. 10.1109\/CVPR He Kaiming, Zhang Xiangyu, Ren Shaoqing, Sun Jian.2016.Deep residual learning for image recognition.In Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition ( CVPR ). IEEE, Las Vegas, USA, 770-778. https:\/\/doi.org\/10.1109\/CVPR. 2016. 90.","journal-title":"Las Vegas, USA"},{"volume-title":"In\u00a0Proceedings of the European conference on computer vision (ECCV)\u00a0.Springer,LNIP 11211","author":"Sanghyun Woo","key":"e_1_3_2_1_19_1","unstructured":"Woo Sanghyun , Park Jongchan , Lee Joon-Young , Kweon In So .2018.CBAM:Convolutional block attention module . In\u00a0Proceedings of the European conference on computer vision (ECCV)\u00a0.Springer,LNIP 11211 ,Cham,3-19. https:\/\/doi.org\/10.1007\/978-3-030-01234-2_1. 10.1007\/978-3-030-01234-2_1 Woo Sanghyun, Park Jongchan, Lee Joon-Young,Kweon In So.2018.CBAM:Convolutional block attention module. In\u00a0Proceedings of the European conference on computer vision (ECCV)\u00a0.Springer,LNIP 11211,Cham,3-19. https:\/\/doi.org\/10.1007\/978-3-030-01234-2_1."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1651\/1\/012169"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Hu Jingfei Wang Hua Gao Shengbo Bao Mingkun Liu Tao Wang Yaxing Zhang Jicong.2019.S-unet: A bridge-style u-net framework with a saliency mechanism for retinal vessel segmentation.\u00a0IEEE Access.7 174167-174177. https:\/\/doi.org\/10.1109\/ACCESS.2019.2940476.    10.1109\/ACCESS.2019.2940476\nHu Jingfei Wang Hua Gao Shengbo Bao Mingkun Liu Tao Wang Yaxing Zhang Jicong.2019.S-unet: A bridge-style u-net framework with a saliency mechanism for retinal vessel segmentation.\u00a0IEEE Access.7 174167-174177. https:\/\/doi.org\/10.1109\/ACCESS.2019.2940476.","DOI":"10.1109\/ACCESS.2019.2940476"},{"key":"e_1_3_2_1_22_1","article-title":"Image segmentation based on improved unet","volume":"1815","author":"Xiaojin Li","year":"2021","unstructured":"Li Xiaojin , Qian Wenhua , Xu Dan , Liu, Chunyun. 2021 . Image segmentation based on improved unet . In\u00a0Journal of Physics: Conference Series. 1815 ,1( February 2021),012018.https:\/\/doi.org\/10.1088\/1742-6596\/1815\/1\/012018. 10.1088\/1742-6596 Li Xiaojin, Qian Wenhua, Xu Dan, Liu, Chunyun.2021.Image segmentation based on improved unet. In\u00a0Journal of Physics: Conference Series.1815,1(February 2021),012018.https:\/\/doi.org\/10.1088\/1742-6596\/1815\/1\/012018.","journal-title":"In\u00a0Journal of Physics: Conference Series."},{"issue":"5","key":"e_1_3_2_1_23_1","first-page":"2261","article-title":"Densely connected convolutional networks","volume":"34","author":"Gao Huang","year":"2017","unstructured":"Huang Gao , Liu Zhuang , Laurens van der Maaten , Kilian Q. Weinberger . 2017 . Densely connected convolutional networks . IEEE Computer Society , 34 , 5 , 2261 - 2269 .https:\/\/doi.org\/10.1109\/CVPR.2017.243. 10.1109\/CVPR.2017.243 Huang Gao, Liu Zhuang,Laurens van der Maaten,Kilian Q. Weinberger.2017.Densely connected convolutional networks. IEEE Computer Society,34,5,2261-2269.https:\/\/doi.org\/10.1109\/CVPR.2017.243.","journal-title":"IEEE Computer Society"},{"key":"#cr-split#-e_1_3_2_1_24_1.1","unstructured":"Li Fuhao Zhao Ximei.2022.Nasal cavity and paranasal sinuses tumor segmentation algorithm based on D-Unet neural network.Computer Engineering.48 1(January 2022) 281-287.https:\/\/doi.org\/ 10.19678\/j.issn.1000-3428.0060120. 10.19678\/j.issn.1000-3428.0060120"},{"key":"#cr-split#-e_1_3_2_1_24_1.2","unstructured":"Li Fuhao Zhao Ximei.2022.Nasal cavity and paranasal sinuses tumor segmentation algorithm based on D-Unet neural network.Computer Engineering.48 1(January 2022) 281-287.https:\/\/doi.org\/ 10.19678\/j.issn.1000-3428.0060120."}],"event":{"name":"SPML 2023: 2023 6th International Conference on Signal Processing and Machine Learning","acronym":"SPML 2023","location":"Tianjin China"},"container-title":["2023 6th International Conference on Signal Processing and Machine Learning (SPML)"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3614008.3614030","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3614008.3614030","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:37:27Z","timestamp":1750178247000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3614008.3614030"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,14]]},"references-count":30,"alternative-id":["10.1145\/3614008.3614030","10.1145\/3614008"],"URL":"https:\/\/doi.org\/10.1145\/3614008.3614030","relation":{},"subject":[],"published":{"date-parts":[[2023,7,14]]},"assertion":[{"value":"2023-10-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}