{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,2]],"date-time":"2025-07-02T17:16:37Z","timestamp":1751476597088,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":20,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819756919"},{"type":"electronic","value":"9789819756926"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-97-5692-6_33","type":"book-chapter","created":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T08:02:35Z","timestamp":1722326555000},"page":"371-380","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Combining CNN and Self-attention-Free Transformer Using Local-Global Attention Fusion for Lung Cancer Segmentation"],"prefix":"10.1007","author":[{"given":"Jiancun","family":"Zhou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hulin","family":"Kuang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yahui","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianxin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,7,31]]},"reference":[{"key":"33_CR1","doi-asserted-by":"publisher","unstructured":"Zhu, N., et al.: A Novel Coronavirus from Patients with Pneumonia in China, 2019. N. Engl. J. Med. 382(8), 727\u2013733 (2020). https:\/\/doi.org\/10.1056\/NEJMoa2001017","DOI":"10.1056\/NEJMoa2001017"},{"key":"33_CR2","doi-asserted-by":"publisher","first-page":"60279","DOI":"10.1109\/ACCESS.2023.3285821","volume":"11","author":"I Naseer","year":"2023","unstructured":"Naseer, I., Akram, S., Masood, T., Rashid, M., Jaffar, A.: Lung cancer classification using modified u-net based lobe segmentation and nodule detection. IEEE Access 11, 60279\u201360291 (2023). https:\/\/doi.org\/10.1109\/ACCESS.2023.3285821","journal-title":"IEEE Access"},{"key":"33_CR3","doi-asserted-by":"crossref","unstructured":"Swensen, S.J., et al.: Lung cancer screening with CT: mayo clinic experience. Radiology 226(3), 756\u2013761 (2003). publisher: Radiological Society of North America","DOI":"10.1148\/radiol.2263020036"},{"key":"33_CR4","doi-asserted-by":"publisher","first-page":"75591","DOI":"10.1109\/ACCESS.2019.2921434","volume":"7","author":"W Chen","year":"2019","unstructured":"Chen, W., Wei, H., Peng, S., Sun, J., Qiao, X., Liu, B.: HSN: hybrid segmentation network for small cell lung cancer segmentation. IEEE Access 7, 75591\u201375603 (2019)","journal-title":"IEEE Access"},{"key":"33_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1007\/978-3-030-62469-9_4","volume-title":"Thoracic Image Analysis","author":"U Kamal","year":"2020","unstructured":"Kamal, U., Rafi, A.M., Hoque, R., Wu, J., Hasan, M.K.: Lung cancer tumor region segmentation using recurrent 3d-denseunet. In: Petersen, J., San Jos\u00e9 Est\u00e9par, R., Schmidt-Richberg, A., Gerard, S., Lassen-Schmidt, B., Jacobs, C., Beichel, R., Mori, K. (eds.) TIA 2020. LNCS, vol. 12502, pp. 36\u201347. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-62469-9_4"},{"key":"33_CR6","doi-asserted-by":"publisher","first-page":"678","DOI":"10.1007\/s10278-019-00301-4","volume":"33","author":"G Singadkar","year":"2020","unstructured":"Singadkar, G., Mahajan, A., Thakur, M., Talbar, S.: Deep deconvolutional residual network based automatic lung nodule segmentation. J. Digit. Imaging 33, 678\u2013684 (2020)","journal-title":"J. Digit. Imaging"},{"issue":"11","key":"33_CR7","doi-asserted-by":"publisher","first-page":"3311","DOI":"10.1007\/s11517-022-02667-0","volume":"60","author":"G Zhang","year":"2022","unstructured":"Zhang, G., Yang, Z., Jiang, S.: Automatic lung tumor segmentation from CT images using improved 3D densely connected UNet. Med. Biol. Eng. Compu. 60(11), 3311\u20133323 (2022)","journal-title":"Med. Biol. Eng. Compu."},{"key":"33_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.105161","volume":"141","author":"P Dutande","year":"2022","unstructured":"Dutande, P., Baid, U., Talbar, S.: Deep residual separable convolutional neural network for lung tumor segmentation. Comput. Biol. Med. 141, 105161 (2022)","journal-title":"Comput. Biol. Med."},{"key":"33_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1007\/978-3-030-87193-2_2","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2021","author":"Y Zhang","year":"2021","unstructured":"Zhang, Y., Liu, H., Hu, Q.: Transfuse: Fusing transformers and cnns for medical image segmentation. In: de Bruijne, M., Cattin, P.C., Cotin, S., Padoy, N., Speidel, S., Zheng, Y., Essert, C. (eds.) MICCAI 2021. LNCS, vol. 12901, pp. 14\u201324. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-87193-2_2"},{"key":"33_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1007\/978-3-030-87193-2_11","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2021","author":"W Wang","year":"2021","unstructured":"Wang, W., Chen, C., Ding, M., Yu, H., Zha, S., Li, J.: Transbts: Multimodal brain tumor segmentation using transformer. In: de Bruijne, M., Cattin, P.C., Cotin, S., Padoy, N., Speidel, S., Zheng, Y., Essert, C. (eds.) MICCAI 2021. LNCS, vol. 12901, pp. 109\u2013119. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-87193-2_11"},{"key":"33_CR11","doi-asserted-by":"crossref","unstructured":"Zhang, Q., Xu, Y., Zhang, J., Tao, D.: ViTAEv2: Vision transformer advanced by exploring inductive bias for image recognition and beyond (2022). arXiv preprint arXiv:2202.10108","DOI":"10.1007\/s11263-022-01739-w"},{"key":"33_CR12","unstructured":"Si, C., Yu, W., Zhou, P., Zhou, Y., Wang, X., Yan, S.: Inception transformer (2022). arXiv preprint arXiv:2205.12956"},{"key":"33_CR13","unstructured":"Chen, J., et al.: TransUNet: Transformers make strong encoders for medical image segmentation (2021). arXiv preprint arXiv:2102.04306"},{"key":"33_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1007\/978-3-030-87199-4_16","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2021","author":"Y Xie","year":"2021","unstructured":"Xie, Y., Zhang, J., Shen, C., Xia, Y.: Cotr: Efficiently bridging cnn and transformer for 3d medical image segmentation. In: de Bruijne, M., Cattin, P.C., Cotin, S., Padoy, N., Speidel, S., Zheng, Y., Essert, C. (eds.) MICCAI 2021. LNCS, vol. 12903, pp. 171\u2013180. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-87199-4_16"},{"key":"33_CR15","unstructured":"Zhou, H.Y., Guo, J., Zhang, Y., Yu, L., Wang, L., Yu, Y.: nnFormer: Interleaved Transformer for Volumetric Segmentation (2022). arXiv:2109.03201"},{"key":"33_CR16","doi-asserted-by":"crossref","unstructured":"Hatamizadeh, A., et al.: UNETR: transformers for 3D medical image segmentation. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 574\u2013584 (2022)","DOI":"10.1109\/WACV51458.2022.00181"},{"key":"33_CR17","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1007\/978-3-031-16443-9_23","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2022: 25th International Conference, Singapore, September 18\u201322, 2022, Proceedings, Part V","author":"W Liu","year":"2022","unstructured":"Liu, W., et al.: PHTrans: Parallelly Aggregating Global and\u00a0Local Representations for\u00a0Medical Image Segmentation. In: Wang, L., Qi Dou, P., Fletcher, T., Speidel, S., Li, S. (eds.) Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2022: 25th International Conference, Singapore, September 18\u201322, 2022, Proceedings, Part V, pp. 235\u2013244. Springer Nature Switzerland, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16443-9_23"},{"key":"33_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109432","volume":"138","author":"Q Yan","year":"2023","unstructured":"Yan, Q., et al.: 3D medical image segmentation using parallel transformers. Pattern Recogn. 138, 109432 (2023)","journal-title":"Pattern Recogn."},{"key":"33_CR19","doi-asserted-by":"crossref","unstructured":"Isensee, F., Jaeger, P.F., Kohl, S.A.A., Petersen, J., Maier-Hein, K.H.: nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat. Methods 18(2), 203\u2013211 (2021)","DOI":"10.1038\/s41592-020-01008-z"},{"key":"33_CR20","doi-asserted-by":"crossref","unstructured":"Wu, B., et al.: Shift: A zero flop, zero parameter alternative to spatial convolutions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 9127\u20139135 (2018)","DOI":"10.1109\/CVPR.2018.00951"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-5692-6_33","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T08:13:36Z","timestamp":1722327216000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-5692-6_33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819756919","9789819756926"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-5692-6_33","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"31 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tianjin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 August 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 August 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2024\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}