{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T19:40:18Z","timestamp":1757619618618,"version":"3.44.0"},"publisher-location":"Singapore","reference-count":22,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819500086"},{"type":"electronic","value":"9789819500093"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-981-95-0009-3_8","type":"book-chapter","created":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T13:25:46Z","timestamp":1753363546000},"page":"86-97","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["UBDet: An Unsupervised Breast Tumor Detection Framework with Boundary-Aware Enhancement"],"prefix":"10.1007","author":[{"given":"Xingxin","family":"Guo","sequence":"first","affiliation":[]},{"given":"Zhihui","family":"Lai","sequence":"additional","affiliation":[]},{"given":"Heng","family":"Kong","sequence":"additional","affiliation":[]},{"given":"Xiaoling","family":"Luo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,7,25]]},"reference":[{"key":"8_CR1","doi-asserted-by":"crossref","unstructured":"Kang, M., Ting, C.-M., Ting, F.F., Phan, R.C.-W.: RCS-YOLO: a fast and high-accuracy object detector for brain tumor detection. In: International Conference on Medical Image Computing and Computer Assisted Intervention, pp. 600\u2013610. Springer, Cham (2023)","DOI":"10.1007\/978-3-031-43901-8_57"},{"key":"8_CR2","doi-asserted-by":"crossref","unstructured":"Tang, Y., et al.: Transfer learning from tumors to organs at risk for cervical cancer image segmentation. In: International Conference on Intelligent Computing, pp. 233\u2013244. Springer, Cham (2024)","DOI":"10.1007\/978-981-97-5578-3_19"},{"key":"8_CR3","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., Fei-Fei, L.: Imagenet: a large-scale hierarchical image database. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 248\u2013255 (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"8_CR4","doi-asserted-by":"crossref","unstructured":"Lin, T.-Y., et al.: Microsoft COCO: common objects in context. In: European Conference on Computer Vision, pp. 740\u2013755 (2014)","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"8_CR5","doi-asserted-by":"crossref","unstructured":"Sato, M., Jin, Z., Suzuki, K.: Semantic segmentation of liver tumor in contrast-enhanced hepatic CT by using deep learning with hessian-based enhancer with small training dataset size. In: 2021 IEEE International Symposium on Biomedical Imaging (ISBI), pp. 34\u201337 (2021)","DOI":"10.1109\/ISBI48211.2021.9433929"},{"key":"8_CR6","doi-asserted-by":"crossref","unstructured":"Sanchez, K., et al.: Subspace-based domain adaptation using similarity constraints for pneumonia diagnosis within a small chest x-ray image dataset. In: 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), pp. 1232\u20131235. IEEE (2021)","DOI":"10.1109\/ISBI48211.2021.9434173"},{"key":"8_CR7","doi-asserted-by":"crossref","unstructured":"Gozes, O., Greenspan, H.: Deep feature learning from a hospital-scale chest x-ray dataset with application to TB detection on a small-scale dataset. In: 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 4076\u20134079. IEEE (2019)","DOI":"10.1109\/EMBC.2019.8856729"},{"key":"8_CR8","doi-asserted-by":"crossref","unstructured":"Huang, K., Zhang, Y., Cheng, H.-D., Xing, P.: Shape-adaptive convolutional operator for breast ultrasound image segmentation. In: 2021 IEEE International Conference on Multimedia and Expo (ICME), pp. 1\u20136. IEEE (2021)","DOI":"10.1109\/ICME51207.2021.9428287"},{"key":"8_CR9","doi-asserted-by":"crossref","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans. Pattern Anal. Mach. Intell. 1137\u20131149 (2017)","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"8_CR10","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: unified, real-time object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 779\u2013788 (2016)","DOI":"10.1109\/CVPR.2016.91"},{"key":"8_CR11","doi-asserted-by":"crossref","unstructured":"Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., Zagoruyko, S.: End-to-end object detection with transformers. In: European Conference on Computer Vision, pp. 213\u2013229. Springer, Cham (2020)","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"8_CR12","doi-asserted-by":"publisher","first-page":"106762","DOI":"10.1016\/j.bspc.2024.106762","volume":"98","author":"Y-T Zhou","year":"2024","unstructured":"Zhou, Y.-T., Yang, T.-Y., Han, X.-H., Piao, J.-C.: Thyroid-DETR: thyroid-DETR: thyroid nodule detection model with transformer in ultrasound images. Biomed. Signal Process. Control 98, 106762 (2024)","journal-title":"Biomed. Signal Process. Control"},{"key":"8_CR13","doi-asserted-by":"crossref","unstructured":"Caron, M., et al.: Emerging properties in self-supervised vision transformers. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9650\u20139660 (2021)","DOI":"10.1109\/ICCV48922.2021.00951"},{"key":"8_CR14","doi-asserted-by":"crossref","unstructured":"Wang, Y., et al.: Tokencut: segmenting objects in images and videos with self-supervised transformer and normalized cut. IEEE Trans. Pattern Anal. Mach. Intell. 15790\u201315801 (2023)","DOI":"10.1109\/TPAMI.2023.3305122"},{"key":"8_CR15","doi-asserted-by":"crossref","unstructured":"Wang, X., et al.: Freesolo: learning to segment objects without annotations. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 14176\u201314186 (2022)","DOI":"10.1109\/CVPR52688.2022.01378"},{"key":"8_CR16","doi-asserted-by":"crossref","unstructured":"Wang, X., Girdhar, R., Yu, S.X., Misra, I.: Cut and learn for unsupervised object detection and instance segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3124\u20133134 (2023)","DOI":"10.1109\/CVPR52729.2023.00305"},{"key":"8_CR17","doi-asserted-by":"publisher","first-page":"888","DOI":"10.1109\/34.868688","volume":"22","author":"J Shi","year":"2000","unstructured":"Shi, J., Malik, J.: Normalized cuts and image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 22, 888\u2013905 (2000)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"8_CR18","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: convolutional networks for biomedical image segmentation. In: International Conference on Medical Image Computing and Computer Assisted Intervention, pp. 234\u2013241 (2015)","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"8_CR19","doi-asserted-by":"crossref","unstructured":"Wang, H., Wu, X., Huang, Z., Xing, E.P.: High-frequency component helps explain the generalization of convolutional neural networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8684\u20138694 (2020)","DOI":"10.1109\/CVPR42600.2020.00871"},{"key":"8_CR20","doi-asserted-by":"publisher","first-page":"104863","DOI":"10.1016\/j.dib.2019.104863","volume":"28","author":"W Al-Dhabyani","year":"2020","unstructured":"Al-Dhabyani, W., Gomaa, M., Khaled, H., Fahmy, A.: Dataset of breast ultrasound images. Data Brief 28, 104863 (2020)","journal-title":"Data Brief"},{"key":"8_CR21","unstructured":"Jocher, G., Qiu, J., Chaurasia, A.: Ultralytics YOLO (2023). https:\/\/github.com\/ultralytics\/ultralytics"},{"key":"8_CR22","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"}],"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\/978-981-95-0009-3_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,7]],"date-time":"2025-09-07T22:41:46Z","timestamp":1757284906000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-0009-3_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819500086","9789819500093"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-0009-3_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"25 July 2025","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","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"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":"Ningbo","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":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/icg\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}