{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T20:10:03Z","timestamp":1784146203265,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":23,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819234844","type":"print"},{"value":"9789819234851","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T00:00:00Z","timestamp":1784160000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T00:00:00Z","timestamp":1784160000000},"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":[[2027]]},"DOI":"10.1007\/978-981-92-3485-1_26","type":"book-chapter","created":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T20:00:33Z","timestamp":1784145633000},"page":"305-317","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["PVGhost-YOLO: A Lightweight Pulmonary Nodule Detection Method with Enhanced Feature Representation"],"prefix":"10.1007","author":[{"given":"Dong","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiajun","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,16]]},"reference":[{"key":"26_CR1","unstructured":"Wild, C.P., Weiderpass, E., Stewart, B.W.: World cancer report. World Cancer Report: cancer research for cancer prevention (2020)"},{"key":"26_CR2","unstructured":"Jocher, G., Qiu, J., Chaurasia, A.: Ultralytics YOLO (2023). https:\/\/github.com\/ultralytics\/ultralytics"},{"key":"26_CR3","unstructured":"Tian, Y., Ye, Q., Doermann, D.: Yolov12: attention-centric real-time object detectors (2025). arXiv preprint arXiv:2502.12524"},{"key":"26_CR4","doi-asserted-by":"publisher","first-page":"76371","DOI":"10.1109\/ACCESS.2023.3296530","volume":"11","author":"Z Ji","year":"2023","unstructured":"Ji, Z., et al.: Lung nodule detection in medical images based on improved YOLOv5s. IEEE Access. 11, 76371\u201376387 (2023)","journal-title":"IEEE Access."},{"key":"26_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2024.111294","volume":"161","author":"C Tang","year":"2025","unstructured":"Tang, C., Zhou, F., Sun, J., Zhang, Y.: Circle-YOLO: an anchor-free lung nodule detection algorithm using bounding circle representation. Pattern Recogn. 161, 111294 (2025)","journal-title":"Pattern Recogn."},{"key":"26_CR6","doi-asserted-by":"crossref","unstructured":"Zhao, Y., et al.: Detrs beat yolos on real-time object detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. pp. 16965\u201316974 (2024)","DOI":"10.1109\/CVPR52733.2024.01605"},{"key":"26_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2025.129827","volume":"633","author":"J Tang","year":"2025","unstructured":"Tang, J., Chen, X., Fan, L., Zhu, Z., Huang, C.: LN-DETR: an efficient transformer architecture for lung nodule detection with multi-scale feature fusion. Neurocomputing 633, 129827 (2025)","journal-title":"Neurocomputing"},{"key":"26_CR8","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 7132\u20137141 (2018)","DOI":"10.1109\/CVPR.2018.00745"},{"key":"26_CR9","doi-asserted-by":"publisher","first-page":"9969","DOI":"10.52202\/068431-0724","volume":"35","author":"Y Tang","year":"2022","unstructured":"Tang, Y., Han, K., Guo, J., Xu, C., Xu, C., Wang, Y.: GhostNetv2: enhance cheap operation with long-range attention. Adv. Neural. Inf. Process. Syst. 35, 9969\u20139982 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"26_CR10","doi-asserted-by":"crossref","unstructured":"Zhang, X., Zhou, X., Lin, M., Sun, J.: Shufflenet: an extremely efficient convolutional neural network for mobile devices. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 6848\u20136856 (2018)","DOI":"10.1109\/CVPR.2018.00716"},{"key":"26_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2025.107830","volume":"107","author":"Z Liu","year":"2025","unstructured":"Liu, Z., Wei, L., Song, T.: Optimized YOLOv11 model for lung nodule detection. Biomed. Signal Process. Control 107, 107830 (2025)","journal-title":"Biomed. Signal Process. Control"},{"key":"26_CR12","doi-asserted-by":"crossref","unstructured":"Hou, Q., Zhou, D., Feng, J.: Coordinate attention for efficient mobile network design. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 13713\u201313722 (2021)","DOI":"10.1109\/CVPR46437.2021.01350"},{"key":"26_CR13","doi-asserted-by":"publisher","first-page":"356","DOI":"10.1038\/nn.4244","volume":"19","author":"DL Yamins","year":"2016","unstructured":"Yamins, D.L., DiCarlo, J.J.: Using goal-driven deep learning models to understand sensory cortex. Nat. Neurosci. 19, 356\u2013365 (2016)","journal-title":"Nat. Neurosci."},{"key":"26_CR14","unstructured":"Roy, O., Vetterli, M.: The effective rank: a measure of effective dimensionality. In: 2007 15th European Signal Processing Conference. pp. 606\u2013610. IEEE (2007)"},{"key":"26_CR15","unstructured":"Nguyen, T., Raghu, M., Kornblith, S.: Do wide and deep networks learn the same things? Uncovering how neural network representations vary with width and depth. In: International Conference on Learning Representations (2021)"},{"key":"26_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.media.2017.06.015","volume":"42","author":"AAA Setio","year":"2017","unstructured":"Setio, A.A.A., et al.: Others: validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge. Med. Image Anal. 42, 1\u201313 (2017)","journal-title":"Med. Image Anal."},{"key":"26_CR17","doi-asserted-by":"publisher","first-page":"915","DOI":"10.1118\/1.3528204","volume":"38","author":"SG Armato III","year":"2011","unstructured":"Armato, S.G., III., et al.: Others: the lung image database consortium (LIDC) and image database resource initiative (IDRI): A completed reference database of lung nodules on CT scans. Med. Phys. 38, 915\u2013931 (2011)","journal-title":"Med. Phys."},{"key":"26_CR18","doi-asserted-by":"crossref","unstructured":"Wang, C.-Y., Yeh, I.-H., Mark Liao, H.-Y.: Yolov9: learning what you want to learn using programmable gradient information. In: European Conference on Computer Vision. pp. 1\u201321. Springer (2024)","DOI":"10.1007\/978-3-031-72751-1_1"},{"key":"26_CR19","doi-asserted-by":"publisher","first-page":"107984","DOI":"10.52202\/079017-3429","volume":"37","author":"A Wang","year":"2024","unstructured":"Wang, A., Chen, H., Liu, L., Chen, K., Lin, Z., Han, J.: Others: Yolov10: real-time end-to-end object detection. Adv. Neural. Inf. Process. Syst. 37, 107984\u2013108011 (2024)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"26_CR20","unstructured":"Khanam, R., Hussain, M.: Yolov11: an overview of the key architectural enhancements (2024). arXiv preprint arXiv:2410.17725"},{"key":"26_CR21","doi-asserted-by":"crossref","unstructured":"Cheng, T., Song, L., Ge, Y., Liu, W., Wang, X., Shan, Y.: Yolo-world: real-time open-vocabulary object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 16901\u201316911 (2024)","DOI":"10.1109\/CVPR52733.2024.01599"},{"key":"26_CR22","unstructured":"Zhu, X., Su, W., Lu, L., Li, B., Wang, X., Dai, J.: Deformable detr: deformable transformers for end-to-end object detection (2020). arXiv preprint arXiv:2010.04159"},{"key":"26_CR23","doi-asserted-by":"crossref","unstructured":"Selvaraju, R.R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., Batra, D.: Grad-cam: visual explanations from deep networks via gradient-based localization. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 618\u2013626 (2017)","DOI":"10.1109\/ICCV.2017.74"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-3485-1_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T20:00:35Z","timestamp":1784145635000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-3485-1_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,16]]},"ISBN":["9789819234844","9789819234851"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-3485-1_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,16]]},"assertion":[{"value":"16 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","label":"Disclosure of Interests","group":{"name":"EthicsHeading","label":"Ethics"}},{"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":"Toronto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2026a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2026\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}