{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T19:46:20Z","timestamp":1765568780572,"version":"3.48.0"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2025,2,4]],"date-time":"2025-02-04T00:00:00Z","timestamp":1738627200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,2,4]],"date-time":"2025-02-04T00:00:00Z","timestamp":1738627200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100004735","name":"Natural Science Foundation of Hunan Province","doi-asserted-by":"publisher","award":["2023JJ30966"],"award-info":[{"award-number":["2023JJ30966"]}],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Digit Imaging. Inform. med."],"DOI":"10.1007\/s10278-025-01428-3","type":"journal-article","created":{"date-parts":[[2025,2,4]],"date-time":"2025-02-04T16:11:49Z","timestamp":1738685509000},"page":"4059-4074","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep-Optimal Leucorrhea Detection Through Fluorescent Benchmark Data Analysis"],"prefix":"10.1007","volume":"38","author":[{"given":"Shuang","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Akam M.","family":"Omer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuping","family":"Duan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Fang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kamyar Othman","family":"Hamad","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mauricio","family":"Fernandez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruiqing","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianghua","family":"Wen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanping","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingang","family":"Cai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangchao","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingying","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fang","family":"Yi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianqiao","family":"Meng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiqun","family":"Mao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4581-0686","authenticated-orcid":false,"given":"Yuxia","family":"Duan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,2,4]]},"reference":[{"key":"1428_CR1","doi-asserted-by":"publisher","first-page":"1896","DOI":"10.1056\/NEJM199712253372607","volume":"337","author":"JD Sobel","year":"1997","unstructured":"J.D. Sobel, Vaginitis, New England Journal of Medicine 337 (1997) 1896\u20131903. https:\/\/doi.org\/10.1056\/NEJM199712253372607.","journal-title":"New England Journal of Medicine"},{"key":"1428_CR2","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1146\/annurev-micro-092611-150157","volume":"66","author":"B Ma","year":"2012","unstructured":"B. Ma, L.J. Forney, J. Ravel, Vaginal Microbiome: Rethinking Health and Disease, Annual Review of Microbiology 66 (2012) 371\u2013389. https:\/\/doi.org\/10.1146\/annurev-micro-092611-150157.","journal-title":"Annual Review of Microbiology"},{"key":"1428_CR3","unstructured":"B.L. Hainer, M.V. Gibson, Vaginitis: Diagnosis and Treatment, Afp 83 (2011) 807\u2013815. https:\/\/www.aafp.org\/pubs\/afp\/issues\/2011\/0401\/p807.html (accessed September 5, 2023)."},{"key":"1428_CR4","doi-asserted-by":"publisher","first-page":"1306","DOI":"10.1136\/bmj.328.7451.1306","volume":"328","author":"H Mitchell","year":"2004","unstructured":"H. Mitchell, Vaginal discharge\u2014causes, diagnosis, and treatment, BMJ 328 (2004) 1306\u20131308. https:\/\/doi.org\/10.1136\/bmj.328.7451.1306.","journal-title":"BMJ"},{"key":"1428_CR5","doi-asserted-by":"publisher","unstructured":"H. Brown, M. Drexler, Improving the Diagnosis of Vulvovaginitis: Perspectives to Align Practice, Guidelines, and Awareness, Popul Health Manag 23 (2020) S-3-S-12. https:\/\/doi.org\/10.1089\/pop.2020.0265.","DOI":"10.1089\/pop.2020.0265"},{"key":"1428_CR6","doi-asserted-by":"publisher","first-page":"431","DOI":"10.3969\/j.issn.2095-5227.2022.04.012","volume":"43","author":"Q Zhai","year":"2022","unstructured":"Q. Zhai, L. Li, X. Wang, Y. Fan, D. Yu, Y. Fu, J. Li, S. Jiang, Clinical evaluation of GY66 automatic vaginal microecological morphology detector, Acad J Chin PLA Med Sch 43 (2022) 431\u2013435. https:\/\/doi.org\/10.3969\/j.issn.2095-5227.2022.04.012.","journal-title":"Acad J Chin PLA Med Sch"},{"key":"1428_CR7","doi-asserted-by":"publisher","unstructured":"S. Fan, T. Li, CDC 2015 guideline for the diagnosis and treatment of vaginal infection, Chinese General Practice 18 (2015) 3046\u20133049. https:\/\/doi.org\/10.3969\/j.issn.1007-9572.2015.25.010","DOI":"10.3969\/j.issn.1007-9572.2015.25.010"},{"key":"1428_CR8","doi-asserted-by":"publisher","unstructured":"C. van der Schee, A. van Belkum, L. Zwijgers, E. van der Brugge, E.L. O\u2019neill, A. Luijendijk, T. van Rijvezel-Vos, Willem I., der Meijden, Henri, Verbrugh, Hans JF, Sluiters, Improved Diagnosis of Trichomonas vaginalis Infection by PCR Using Vaginal Swabs and Urine Specimens Compared to Diagnosis by Wet Mount Microscopy, Culture, and Fluorescent Staining, Journal of Clinical Microbiology 37 (1999) 4127\u20134130. https:\/\/doi.org\/10.1128\/jcm.37.12.4127-4130.1999.","DOI":"10.1128\/jcm.37.12.4127-4130.1999"},{"key":"1428_CR9","unstructured":"N. Tripathi, A. Sapra, Gram Staining, in: StatPearls, StatPearls Publishing, Treasure Island (FL), 2023. http:\/\/www.ncbi.nlm.nih.gov\/books\/NBK562156\/ (accessed October 19, 2023)."},{"key":"1428_CR10","doi-asserted-by":"publisher","first-page":"1312","DOI":"10.1007\/s11426-019-9508-6","volume":"62","author":"Y Zhou","year":"2019","unstructured":"Y. Zhou, J. Hua, B.Z. Tang, Y. Tang, AIEgens in cell-based multiplex fluorescence imaging, Sci. China Chem. 62 (2019) 1312\u20131332. https:\/\/doi.org\/10.1007\/s11426-019-9508-6.","journal-title":"Sci. China Chem."},{"key":"1428_CR11","doi-asserted-by":"publisher","first-page":"1215","DOI":"10.1038\/s41592-019-0458-z","volume":"16","author":"C Belthangady","year":"2019","unstructured":"C. Belthangady, L.A. Royer, Applications, promises, and pitfalls of deep learning for fluorescence image reconstruction, Nat Methods 16 (2019) 1215\u20131225. https:\/\/doi.org\/10.1038\/s41592-019-0458-z.","journal-title":"Nat Methods"},{"key":"1428_CR12","doi-asserted-by":"publisher","unstructured":"C. Li, Z. Duan, C. Ying, Application value of double fluorescence staining method in the diagnosis of gynecological vaginitis, Maternal and Child Health Care of China 37 (2022) 2734\u20132737. https:\/\/doi.org\/10.19829\/j.zgfybj.issn.1001-4411.2022.15.006.","DOI":"10.19829\/j.zgfybj.issn.1001-4411.2022.15.006"},{"key":"1428_CR13","doi-asserted-by":"publisher","first-page":"1837","DOI":"10.1109\/JBHI.2020.2991043","volume":"24","author":"AS Panayides","year":"2020","unstructured":"A.S. Panayides, A. Amini, N.D. Filipovic, A. Sharma, S.A. Tsaftaris, A. Young, D. Foran, N. Do, S. Golemati, T. Kurc, K. Huang, K.S. Nikita, B.P. Veasey, M. Zervakis, J.H. Saltz, C.S. Pattichis, AI in Medical Imaging Informatics: Current Challenges and Future Directions, IEEE Journal of Biomedical and Health Informatics 24 (2020) 1837\u20131857. https:\/\/doi.org\/10.1109\/JBHI.2020.2991043.","journal-title":"IEEE Journal of Biomedical and Health Informatics"},{"key":"1428_CR14","doi-asserted-by":"publisher","first-page":"102691","DOI":"10.1016\/j.media.2022.102691","volume":"84","author":"H Jiang","year":"2023","unstructured":"H. Jiang, Y. Zhou, Y. Lin, R.C.K. Chan, J. Liu, H. Chen, Deep learning for computational cytology: A survey, Medical Image Analysis 84 (2023) 102691. https:\/\/doi.org\/10.1016\/j.media.2022.102691.","journal-title":"Medical Image Analysis"},{"key":"1428_CR15","doi-asserted-by":"publisher","first-page":"105636","DOI":"10.1016\/j.compbiomed.2022.105636","volume":"146","author":"W He","year":"2022","unstructured":"W. He, T. Liu, Y. Han, W. Ming, J. Du, Y. Liu, Y. Yang, L. Wang, Z. Jiang, Y. Wang, J. Yuan, C. Cao, A review: The detection of cancer cells in histopathology based on machine vision, Computers in Biology and Medicine 146 (2022) 105636. https:\/\/doi.org\/10.1016\/j.compbiomed.2022.105636.","journal-title":"Computers in Biology and Medicine"},{"key":"1428_CR16","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-024-01226-3","author":"R Zhang","year":"2024","unstructured":"R. Zhang, C. Pei, J. Shi, S. Wang, Construction and Validation of a General Medical Image Dataset for Pretraining, J Digit Imaging. Inform. Med. (2024). https:\/\/doi.org\/10.1007\/s10278-024-01226-3.","journal-title":"J Digit Imaging. Inform. Med."},{"key":"1428_CR17","doi-asserted-by":"publisher","unstructured":"S. Peng, H. Huang, M. Cheng, Y. Yang, F. Li, Efficiently recognition of vaginal micro-ecological environment based on Convolutional Neural Network, in: 2020 IEEE International Conference on E-Health Networking, Application & Services (HEALTHCOM), 2021: pp. 1\u20136. https:\/\/doi.org\/10.1109\/HEALTHCOM49281.2021.9399040.","DOI":"10.1109\/HEALTHCOM49281.2021.9399040"},{"key":"1428_CR18","doi-asserted-by":"publisher","first-page":"e02236","DOI":"10.1128\/JCM.02236-20","volume":"59","author":"Z Wang","year":"2021","unstructured":"Z. Wang, L. Zhang, M. Zhao, Y. Wang, H. Bai, Y. Wang, C. Rui, C. Fan, J. Li, N. Li, X. Liu, Z. Wang, Y. Si, A. Feng, M. Li, Q. Zhang, Z. Yang, M. Wang, W. Wu, Y. Cao, L. Qi, X. Zeng, L. Geng, R. An, P. Li, Z. Liu, Q. Qiao, W. Zhu, W. Mo, Q. Liao, W. Xu, Deep Neural Networks Offer Morphologic Classification and Diagnosis of Bacterial Vaginosis, Journal of Clinical Microbiology 59 (2021) e02236-20. https:\/\/doi.org\/10.1128\/JCM.02236-20.","journal-title":"Journal of Clinical Microbiology"},{"key":"1428_CR19","doi-asserted-by":"publisher","first-page":"1132","DOI":"10.3390\/s22031132","volume":"22","author":"K Zhao","year":"2022","unstructured":"K. Zhao, P. Gao, S. Liu, Y. Wang, G. Li, Y. Wang, A Vaginitis Classification Method Based on Multi-Spectral Image Feature Fusion, Sensors 22 (2022) 1132. https:\/\/doi.org\/10.3390\/s22031132.","journal-title":"Sensors"},{"key":"1428_CR20","doi-asserted-by":"publisher","first-page":"100008","DOI":"10.1016\/j.tbench.2021.100008","volume":"1","author":"L Li","year":"2021","unstructured":"L. Li, J. Liu, F. Yu, X. Wang, T.-Z. Xiang, MVDI25K: A large-scale dataset of microscopic vaginal discharge images, BenchCouncil Transactions on Benchmarks, Standards and Evaluations 1 (2021) 100008. https:\/\/doi.org\/10.1016\/j.tbench.2021.100008.","journal-title":"BenchCouncil Transactions on Benchmarks, Standards and Evaluations"},{"key":"1428_CR21","doi-asserted-by":"publisher","first-page":"1229","DOI":"10.1109\/JBHI.2021.3101886","volume":"26","author":"X Du","year":"2022","unstructured":"X. Du, X. Wang, G. Ni, J. Zhang, R. Hao, J. Zhao, X. Wang, J. Liu, L. Liu, SDoF-Net: Super Depth of Field Network for Cell Detection in Leucorrhea Micrograph, IEEE Journal of Biomedical and Health Informatics 26 (2022) 1229\u20131238. https:\/\/doi.org\/10.1109\/JBHI.2021.3101886.","journal-title":"IEEE Journal of Biomedical and Health Informatics"},{"key":"1428_CR22","doi-asserted-by":"publisher","unstructured":"Z. Zou, K. Chen, Z. Shi, Y. Guo, J. Ye, Object Detection in 20 Years: A Survey, Proceedings of the IEEE (2023) 1\u201320. https:\/\/doi.org\/10.1109\/JPROC.2023.3238524.","DOI":"10.1109\/JPROC.2023.3238524"},{"key":"1428_CR23","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1109\/TPAMI.2022.3152247","volume":"45","author":"K Han","year":"2023","unstructured":"K. Han, Y. Wang, H. Chen, X. Chen, J. Guo, Z. Liu, Y. Tang, A. Xiao, C. Xu, Y. Xu, Z. Yang, Y. Zhang, D. Tao, A Survey on Vision Transformer, IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (2023) 87\u2013110. https:\/\/doi.org\/10.1109\/TPAMI.2022.3152247.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"1428_CR24","doi-asserted-by":"publisher","first-page":"779","DOI":"10.1109\/CVPR.2016.91","volume":"2016","author":"J Redmon","year":"2016","unstructured":"J. Redmon, S. Divvala, R. Girshick, A. Farhadi, You Only Look Once: Unified, Real-Time Object Detection, in: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016: pp. 779\u2013788. https:\/\/doi.org\/10.1109\/CVPR.2016.91.","journal-title":"IEEE Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"1428_CR25","doi-asserted-by":"publisher","unstructured":"J. Redmon, A. Farhadi, YOLOv3: An Incremental Improvement, (2018). https:\/\/doi.org\/10.48550\/arXiv.1804.02767.","DOI":"10.48550\/arXiv.1804.02767"},{"key":"1428_CR26","doi-asserted-by":"publisher","unstructured":"A. Bochkovskiy, C.-Y. Wang, H.-Y.M. Liao, YOLOv4: Optimal Speed and Accuracy of Object Detection, (2020). https:\/\/doi.org\/10.48550\/arXiv.2004.10934.","DOI":"10.48550\/arXiv.2004.10934"},{"key":"1428_CR27","doi-asserted-by":"publisher","unstructured":"G. Jocher, A. Chaurasia, A. Stoken, J. Borovec, NanoCode012, Y. Kwon, K. Michael, TaoXie, J. Fang, Imyhxy, Lorna, Y. Zeng, C. Wong, A. V, D. Montes, Z. Wang, C. Fati, J. Nadar, Laughing, UnglvKitDe, V. Sonck, Tkianai, YxNONG, P. Skalski, A. Hogan, D. Nair, M. Strobel, M. Jain, ultralytics\/yolov5: v7.0 - YOLOv5 SOTA Realtime Instance Segmentation, Zenodo (2022). https:\/\/doi.org\/10.5281\/zenodo.7347926.","DOI":"10.5281\/zenodo.7347926"},{"key":"1428_CR28","doi-asserted-by":"publisher","unstructured":"C. Li, L. Li, Y. Geng, H. Jiang, M. Cheng, B. Zhang, Z. Ke, X. Xu, X. Chu, YOLOv6 v3.0: A Full-Scale Reloading, (2023). https:\/\/doi.org\/10.48550\/arXiv.2301.05586.","DOI":"10.48550\/arXiv.2301.05586"},{"key":"1428_CR29","doi-asserted-by":"publisher","first-page":"7464","DOI":"10.1109\/CVPR52729.2023.00721","volume":"2023","author":"C-Y Wang","year":"2023","unstructured":"C.-Y. Wang, A. Bochkovskiy, H.-Y.M. Liao, YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors, in: 2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023: pp. 7464\u20137475. https:\/\/doi.org\/10.1109\/CVPR52729.2023.00721.","journal-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"1428_CR30","doi-asserted-by":"publisher","first-page":"5350","DOI":"10.1109\/CVPRW59228.2023.00564","volume":"2023","author":"A Aboah","year":"2023","unstructured":"A. Aboah, B. Wang, U. Bagci, Y. Adu-Gyamfi, Real-time Multi-Class Helmet Violation Detection Using Few-Shot Data Sampling Technique and YOLOv8, in: 2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023: pp. 5350\u20135358. https:\/\/doi.org\/10.1109\/CVPRW59228.2023.00564.","journal-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)"},{"key":"1428_CR31","doi-asserted-by":"publisher","unstructured":"C.-Y. Wang, I.-H. Yeh, H.-Y.M. Liao, YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information, (2024). https:\/\/doi.org\/10.48550\/arXiv.2402.13616.","DOI":"10.48550\/arXiv.2402.13616"},{"key":"1428_CR32","doi-asserted-by":"publisher","unstructured":"A. Wang, H. Chen, L. Liu, K. Chen, Z. Lin, J. Han, G. Ding, YOLOv10: Real-Time End-to-End Object Detection, (2024). https:\/\/doi.org\/10.48550\/arXiv.2405.14458.","DOI":"10.48550\/arXiv.2405.14458"},{"key":"1428_CR33","unstructured":"Glenn Jocher, Jing Qiu. 2024. \u201cUltralyrics YOLO11.\u201dHttps:\/\/Github.Com\/Ultralytics\/Ultralytics., (n.d.)."},{"key":"1428_CR34","doi-asserted-by":"publisher","first-page":"2635","DOI":"10.1007\/s10278-023-00871-4","volume":"36","author":"W Panyarak","year":"2023","unstructured":"W. Panyarak, K. Wantanajittikul, A. Charuakkra, S. Prapayasatok, W. Suttapak, Enhancing Caries Detection in Bitewing Radiographs Using YOLOv7, J Digit Imaging 36 (2023) 2635\u20132647. https:\/\/doi.org\/10.1007\/s10278-023-00871-4.","journal-title":"J Digit Imaging"},{"key":"1428_CR35","unstructured":"S. Ren, K. He, R. Girshick, J. Sun, Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks, in: C. Cortes, N. Lawrence, D. Lee, M. Sugiyama, R. Garnett (Eds.), Advances in Neural Information Processing Systems, Curran Associates, Inc., 2015. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2015\/file\/14bfa6bb14875e45bba028a21ed38046-Paper.pdf."},{"key":"1428_CR36","doi-asserted-by":"publisher","first-page":"6154","DOI":"10.1109\/CVPR.2018.00644","volume":"2018","author":"Z Cai","year":"2018","unstructured":"Z. Cai, N. Vasconcelos, Cascade R-CNN: Delving Into High Quality Object Detection, in: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2018: pp. 6154\u20136162. https:\/\/doi.org\/10.1109\/CVPR.2018.00644.","journal-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition"},{"key":"1428_CR37","doi-asserted-by":"publisher","first-page":"9992","DOI":"10.1109\/ICCV48922.2021.00986","volume":"2021","author":"Z Liu","year":"2021","unstructured":"Z. Liu, Y. Lin, Y. Cao, H. Hu, Y. Wei, Z. Zhang, S. Lin, B. Guo, Swin Transformer: Hierarchical Vision Transformer using Shifted Windows, in: 2021 IEEE\/CVF International Conference on Computer Vision (ICCV), 2021: pp. 9992\u201310002. https:\/\/doi.org\/10.1109\/ICCV48922.2021.00986.","journal-title":"IEEE\/CVF International Conference on Computer Vision (ICCV)"},{"key":"1428_CR38","doi-asserted-by":"publisher","unstructured":"N. Carion, F. Massa, G. Synnaeve, N. Usunier, A. Kirillov, S. Zagoruyko, End-to-End Object Detection with Transformers, in: A. Vedaldi, H. Bischof, T. Brox, J.-M. Frahm (Eds.), Computer Vision \u2013 ECCV 2020, Springer International Publishing, Cham, 2020: pp. 213\u2013229. https:\/\/doi.org\/10.1007\/978-3-030-58452-8_13.","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"1428_CR39","doi-asserted-by":"publisher","first-page":"732","DOI":"10.1017\/S1431927622000265","volume":"28","author":"R Hao","year":"2022","unstructured":"R. Hao, X. Wang, X. Du, J. Zhang, J. Liu, L. Liu, End-to-End Deep Learning-Based Cells Detection in Microscopic Leucorrhea Images, Microscopy and Microanalysis 28 (2022) 732\u2013743. https:\/\/doi.org\/10.1017\/S1431927622000265.","journal-title":"Microscopy and Microanalysis"},{"key":"1428_CR40","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.media.2017.07.005","volume":"42","author":"G Litjens","year":"2017","unstructured":"G. Litjens, T. Kooi, B.E. Bejnordi, A.A.A. Setio, F. Ciompi, M. Ghafoorian, J.A.W.M. van der Laak, B. van Ginneken, C.I. S\u00e1nchez, A survey on deep learning in medical image analysis, Medical Image Analysis 42 (2017) 60\u201388. https:\/\/doi.org\/10.1016\/j.media.2017.07.005.","journal-title":"Medical Image Analysis"},{"key":"1428_CR41","doi-asserted-by":"publisher","first-page":"1577","DOI":"10.1109\/CVPR42600.2020.00165","volume":"2020","author":"K Han","year":"2020","unstructured":"K. Han, Y. Wang, Q. Tian, J. Guo, C. Xu, C. Xu, GhostNet: More Features From Cheap Operations, in: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020: pp. 1577\u20131586. https:\/\/doi.org\/10.1109\/CVPR42600.2020.00165.","journal-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"1428_CR42","doi-asserted-by":"publisher","first-page":"936","DOI":"10.1109\/CVPR.2017.106","volume":"2017","author":"T-Y Lin","year":"2017","unstructured":"T.-Y. Lin, P. Doll\u00e1r, R. Girshick, K. He, B. Hariharan, S. Belongie, Feature Pyramid Networks for Object Detection, in: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017: pp. 936\u2013944. https:\/\/doi.org\/10.1109\/CVPR.2017.106.","journal-title":"IEEE Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"1428_CR43","doi-asserted-by":"publisher","first-page":"764","DOI":"10.1109\/ICCV.2017.89","volume":"2017","author":"J Dai","year":"2017","unstructured":"J. Dai, H. Qi, Y. Xiong, Y. Li, G. Zhang, H. Hu, Y. Wei, Deformable Convolutional Networks, in: 2017 IEEE International Conference on Computer Vision (ICCV), 2017: pp. 764\u2013773. https:\/\/doi.org\/10.1109\/ICCV.2017.89.","journal-title":"IEEE International Conference on Computer Vision (ICCV)"},{"key":"1428_CR44","doi-asserted-by":"publisher","first-page":"13467","DOI":"10.1109\/TPAMI.2023.3290594","volume":"45","author":"G Cheng","year":"2023","unstructured":"G. Cheng, X. Yuan, X. Yao, K. Yan, Q. Zeng, X. Xie, J. Han, Towards Large-Scale Small Object Detection: Survey and Benchmarks, IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (2023) 13467\u201313488. https:\/\/doi.org\/10.1109\/TPAMI.2023.3290594.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"1428_CR45","doi-asserted-by":"publisher","first-page":"1874","DOI":"10.1007\/s10278-024-01070-5","volume":"37","author":"B Pang","year":"2024","unstructured":"B. Pang, L. Chen, Q. Tao, E. Wang, Y. Yu, GA-UNet: A Lightweight Ghost and Attention U-Net for Medical Image Segmentation, J Digit Imaging. Inform. Med. 37 (2024) 1874\u20131888. https:\/\/doi.org\/10.1007\/s10278-024-01070-5.","journal-title":"J Digit Imaging. Inform. Med."},{"key":"1428_CR46","doi-asserted-by":"publisher","unstructured":"C.-Y. Wang, H.-Y. Mark Liao, Y.-H. Wu, P.-Y. Chen, J.-W. Hsieh, I.-H. Yeh, CSPNet: A New Backbone that can Enhance Learning Capability of CNN, in: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020: pp. 1571\u20131580. https:\/\/doi.org\/10.1109\/CVPRW50498.2020.00203.","DOI":"10.1109\/CVPRW50498.2020.00203"},{"key":"1428_CR47","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/ICEngTechnol.2017.8308186","volume":"2017","author":"S Albawi","year":"2017","unstructured":"S. Albawi, T.A. Mohammed, S. Al-Zawi, Understanding of a convolutional neural network, in: 2017 International Conference on Engineering and Technology (ICET), 2017: pp. 1\u20136. https:\/\/doi.org\/10.1109\/ICEngTechnol.2017.8308186.","journal-title":"International Conference on Engineering and Technology (ICET)"},{"key":"1428_CR48","doi-asserted-by":"publisher","unstructured":"Y. Jiang, Z. Tan, J. Wang, X. Sun, M. Lin, H. Li, GiraffeDet: A Heavy-Neck Paradigm for Object Detection, (2022). https:\/\/doi.org\/10.48550\/arXiv.2202.04256.","DOI":"10.48550\/arXiv.2202.04256"},{"key":"1428_CR49","doi-asserted-by":"publisher","first-page":"1057","DOI":"10.1109\/TIP.2020.3042059","volume":"30","author":"Y Wang","year":"2021","unstructured":"Y. Wang, J. Yang, L. Wang, X. Ying, T. Wu, W. An, Y. Guo, Light Field Image Super-Resolution Using Deformable Convolution, IEEE Transactions on Image Processing 30 (2021) 1057\u20131071. https:\/\/doi.org\/10.1109\/TIP.2020.3042059.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1428_CR50","doi-asserted-by":"crossref","unstructured":"T.-Y. Lin, P. Goyal, R. Girshick, K. He, P. Dollar, Focal Loss for Dense Object Detection, in: 2017: pp. 2980\u20132988. https:\/\/openaccess.thecvf.com\/content_iccv_2017\/html\/Lin_Focal_Loss_for_ICCV_2017_paper.html (accessed March 20, 2024).","DOI":"10.1109\/ICCV.2017.324"},{"key":"1428_CR51","doi-asserted-by":"crossref","unstructured":"M. Tan, R. Pang, Q.V. Le, EfficientDet: Scalable and Efficient Object Detection, in: 2020: pp. 10781\u201310790. https:\/\/openaccess.thecvf.com\/content_CVPR_2020\/html\/Tan_EfficientDet_Scalable_and_Efficient_Object_Detection_CVPR_2020_paper.html (accessed March 20, 2024).","DOI":"10.1109\/CVPR42600.2020.01079"},{"key":"1428_CR52","doi-asserted-by":"publisher","unstructured":"W. Lv, Y. Zhao, S. Xu, J. Wei, G. Wang, C. Cui, Y. Du, Q. Dang, Y. Liu, DETRs Beat YOLOs on Real-time Object Detection, (2023). https:\/\/doi.org\/10.48550\/arXiv.2304.08069.","DOI":"10.48550\/arXiv.2304.08069"},{"key":"1428_CR53","doi-asserted-by":"crossref","unstructured":"R.R. Selvaraju, M. Cogswell, A. Das, R. Vedantam, D. Parikh, D. Batra, Grad-CAM: Visual Explanations From Deep Networks via Gradient-Based Localization, in: 2017: pp. 618\u2013626. https:\/\/openaccess.thecvf.com\/content_iccv_2017\/html\/Selvaraju_Grad-CAM_Visual_Explanations_ICCV_2017_paper.html (accessed October 23, 2024).","DOI":"10.1109\/ICCV.2017.74"},{"key":"1428_CR54","doi-asserted-by":"publisher","first-page":"1314","DOI":"10.1109\/ICCV.2019.00140","volume":"2019","author":"A Howard","year":"2019","unstructured":"A. Howard, M. Sandler, B. Chen, W. Wang, L.-C. Chen, M. Tan, G. Chu, V. Vasudevan, Y. Zhu, R. Pang, H. Adam, Q. Le, Searching for MobileNetV3, in: 2019 IEEE\/CVF International Conference on Computer Vision (ICCV), 2019: pp. 1314\u20131324. https:\/\/doi.org\/10.1109\/ICCV.2019.00140.","journal-title":"IEEE\/CVF International Conference on Computer Vision (ICCV)"},{"key":"1428_CR55","doi-asserted-by":"publisher","unstructured":"Y. Tang, K. Han, J. Guo, C. Xu, C. Xu, Y. Wang, GhostNetV2: Enhance Cheap Operation with Long-Range Attention, (2022). https:\/\/doi.org\/10.48550\/arXiv.2211.12905.","DOI":"10.48550\/arXiv.2211.12905"},{"key":"1428_CR56","doi-asserted-by":"publisher","unstructured":"J. Chen, S. Kao, H. He, W. Zhuo, S. Wen, C.-H. Lee, S.-H.G. Chan, Run, Don\u2019t Walk: Chasing Higher FLOPS for Faster Neural Networks, (2023). https:\/\/doi.org\/10.48550\/arXiv.2303.03667.","DOI":"10.48550\/arXiv.2303.03667"},{"key":"1428_CR57","doi-asserted-by":"publisher","unstructured":"H. Li, J. Li, H. Wei, Z. Liu, Z. Zhan, Q. Ren, Slim-neck by GSConv: A better design paradigm of detector architectures for autonomous vehicles, (2022). https:\/\/doi.org\/10.48550\/arXiv.2206.02424.","DOI":"10.48550\/arXiv.2206.02424"}],"container-title":["Journal of Imaging Informatics in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-025-01428-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10278-025-01428-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-025-01428-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T19:24:40Z","timestamp":1765567480000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10278-025-01428-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,4]]},"references-count":57,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["1428"],"URL":"https:\/\/doi.org\/10.1007\/s10278-025-01428-3","relation":{},"ISSN":["2948-2933"],"issn-type":[{"type":"electronic","value":"2948-2933"}],"subject":[],"published":{"date-parts":[[2025,2,4]]},"assertion":[{"value":"1 November 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 January 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 January 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 February 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This work is a retrospective study which conducted on already available data.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics Approval\/Consent to Participate and Publish."}},{"value":"Shuang Li and Yuxia Duan has received research funding for the compilation and deployment of automated recognition algorithms from Shenzhen United Medical Technology Co., LTD. The other authors have no relevant financial or non-financial interests to disclose.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interests"}}]}}