{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T00:07:46Z","timestamp":1758672466719,"version":"3.44.0"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032058249","type":"print"},{"value":"9783032058256","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T00:00:00Z","timestamp":1758672000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T00:00:00Z","timestamp":1758672000000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-05825-6_6","type":"book-chapter","created":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T06:40:40Z","timestamp":1758609640000},"page":"57-67","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Lightweight Dual-Task Framework for\u00a0Semi-supervised Lesion Segmentation with\u00a0Knowledge Distillation from\u00a0SAM"],"prefix":"10.1007","author":[{"given":"Xuan-Loc","family":"Huynh","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huy-Thach","family":"Pham","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anh Mai","family":"Vu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thanh-Minh","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tran Quang Khai","family":"Bui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tat-Bach","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Quan","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minh Huu Nhat","family":"Le","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Phat K.","family":"Huynh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,9,24]]},"reference":[{"issue":"1","key":"6_CR1","doi-asserted-by":"publisher","first-page":"4128","DOI":"10.1038\/s41467-022-30695-9","volume":"13","author":"M Antonelli","year":"2022","unstructured":"Antonelli, M., et al.: The medical segmentation decathlon. Nature Commun. 13(1), 4128 (2022)","journal-title":"The medical segmentation decathlon. Nature Commun."},{"key":"6_CR2","doi-asserted-by":"crossref","unstructured":"Bu, Q., Dong, B., Zhu, Z., Ni, J.: Edge enhancement based semi-supervised medical image segmentation method. In: 2025 2nd International Conference on Digital Image Processing and Computer Applications (DIPCA), pp. 39\u201343. IEEE (2025)","DOI":"10.1109\/DIPCA65051.2025.11042659"},{"key":"6_CR3","doi-asserted-by":"crossref","unstructured":"Chen, X., Yuan, Y., Zeng, G., Wang, J.: Semi-supervised semantic segmentation with cross pseudo supervision. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2613\u20132622 (2021)","DOI":"10.1109\/CVPR46437.2021.00264"},{"key":"6_CR4","doi-asserted-by":"crossref","unstructured":"Codella, N.C., et\u00a0al.: Skin lesion analysis toward melanoma detection: a challenge at the 2017 international symposium on biomedical imaging (isbi), hosted by the international skin imaging collaboration (isic). In: 2018 IEEE 15th international symposium on biomedical imaging (ISBI 2018), pp. 168\u2013172. IEEE (2018)","DOI":"10.1109\/ISBI.2018.8363547"},{"key":"6_CR5","unstructured":"Hinton, G., Vinyals, O., Dean, J.: Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531 (2015)"},{"key":"6_CR6","doi-asserted-by":"crossref","unstructured":"Huang, K., et al.: Learnable prompting sam-induced knowledge distillation for semi-supervised medical image segmentation. IEEE Trans. Med. Imaging (2025)","DOI":"10.1109\/TMI.2025.3530097"},{"key":"6_CR7","first-page":"2803","volume":"35","author":"Y Jin","year":"2022","unstructured":"Jin, Y., Wang, J., Lin, D.: Semi-supervised semantic segmentation via gentle teaching assistant. Adv. Neural. Inf. Process. Syst. 35, 2803\u20132816 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"6_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"552","DOI":"10.1007\/978-3-030-59710-8_54","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2020","author":"S Li","year":"2020","unstructured":"Li, S., Zhang, C., He, X.: Shape-aware semi-supervised 3d semantic segmentation for medical images. In: Martel, A.L., Abolmaesumi, P., Stoyanov, D., Mateus, D., Zuluaga, M.A., Zhou, S.K., Racoceanu, D., Joskowicz, L. (eds.) MICCAI 2020. LNCS, vol. 12261, pp. 552\u2013561. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-59710-8_54"},{"key":"6_CR9","unstructured":"Li, X., Yu, L., Chen, H., Fu, C.W., Heng, P.A.: Semi-supervised skin lesion segmentation via transformation consistent self-ensembling model. arXiv preprint arXiv:1808.03887 (2018)"},{"key":"6_CR10","doi-asserted-by":"crossref","unstructured":"Luu, Q.V., Le, K.D., Nguyen, T.H., Nguyen, T.M., Nguyen, Q., Nguyen, T.T., Dinh, Q.V.: Semi-supervised semantic segmentation using redesigned self-training for white blood cells. In: 2025 IEEE 6th International Conference on Image Processing, Applications and Systems (IPAS), pp.\u00a01\u20136. IEEE (2025)","DOI":"10.1109\/IPAS63548.2025.10924549"},{"key":"6_CR11","doi-asserted-by":"publisher","first-page":"36267","DOI":"10.1109\/ACCESS.2024.3374105","volume":"12","author":"BH Ngo","year":"2024","unstructured":"Ngo, B.H., Lam, B.T., Nguyen, T.H., Dinh, Q.V., Choi, T.J.: Dual dynamic consistency regularization for semi-supervised domain adaptation. IEEE Access 12, 36267\u201336279 (2024). https:\/\/doi.org\/10.1109\/ACCESS.2024.3374105","journal-title":"IEEE Access"},{"key":"6_CR12","doi-asserted-by":"crossref","unstructured":"Nguyen, T.H., Ngo, T.K.N., Vu, M.A., Tu, T.Y.: Blurry-consistency segmentation framework with selective stacking on differential interference contrast 3d breast cancer spheroid. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5223\u20135230 (2024)","DOI":"10.1109\/CVPRW63382.2024.00531"},{"key":"6_CR13","unstructured":"Nguyen, T.H., Nguyen, T., Nguyen, X.B., Vu, N.L.V., Dinh, V.Q., MERIAUDEAU, F.: Semi-supervised skin lesion segmentation under dual mask ensemble with feature discrepancy co-training. In: Medical Imaging with Deep Learning"},{"key":"6_CR14","unstructured":"Nguyen, T.H., Vu, N.L.V., Nguyen, H.T., Dinh, Q.V., Li, X., Xu, M.: Semi-supervised histopathology image segmentation with feature diversified collaborative learning. In: AAAI Bridge Program on AI for Medicine and Healthcare, pp. 165\u2013172. PMLR (2025)"},{"key":"6_CR15","doi-asserted-by":"crossref","unstructured":"Ouali, Y., Hudelot, C., Tami, M.: Semi-supervised semantic segmentation with cross-consistency training. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12674\u201312684 (2020)","DOI":"10.1109\/CVPR42600.2020.01269"},{"key":"6_CR16","doi-asserted-by":"crossref","unstructured":"Pham, H.H., et\u00a0al.: Fetal-bcp: addressing empirical distribution gap in semi-supervised fetal ultrasound segmentation. In: 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI), pp.\u00a01\u20134. IEEE (2025)","DOI":"10.1109\/ISBI60581.2025.10980925"},{"key":"6_CR17","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: convolutional networks for biomedical image segmentation. In: Medical image computing and computer-assisted intervention\u2013MICCAI 2015: 18th international conference, Munich, Germany, October 5-9, 2015, proceedings, part III 18, pp. 234\u2013241. Springer (2015)","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"6_CR18","first-page":"596","volume":"33","author":"K Sohn","year":"2020","unstructured":"Sohn, K., Berthelot, D., Carlini, N., Zhang, Z., Zhang, H., Raffel, C.A., Cubuk, E.D., Kurakin, A., Li, C.L.: Fixmatch: simplifying semi-supervised learning with consistency and confidence. Adv. Neural. Inf. Process. Syst. 33, 596\u2013608 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"issue":"1","key":"6_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/sdata.2018.161","volume":"5","author":"P Tschandl","year":"2018","unstructured":"Tschandl, P., Rosendahl, C., Kittler, H.: The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions. Sci. Data 5(1), 1\u20139 (2018)","journal-title":"Sci. Data"},{"key":"6_CR20","doi-asserted-by":"crossref","unstructured":"Wang, Y., et al.: Deep distance transform for tubular structure segmentation in ct scans. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3833\u20133842 (2020)","DOI":"10.1109\/CVPR42600.2020.00389"},{"key":"6_CR21","doi-asserted-by":"crossref","unstructured":"Wang, Y., Cao, P., Hou, Q., Lan, L., Yang, J., Liu, X., Zaiane, O.R.: Progressively correcting soft labels via teacher team for knowledge distillation in medical image segmentation. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 521\u2013530. Springer (2024)","DOI":"10.1007\/978-3-031-72114-4_50"},{"key":"6_CR22","unstructured":"Wu, J., Fu, R., Fang, H., Liu, Y., Wang, Z., Xu, Y., Jin, Y., Arbel, T.: Medical sam adapter: Adapting segment anything model for medical image segmentation. arxiv 2023. arXiv preprint arXiv:2304.12620 (2023)"},{"key":"6_CR23","doi-asserted-by":"crossref","unstructured":"Xie, Y., Yin, Y., Li, Q., Wang, Y.: Deep mutual distillation for semi-supervised medical image segmentation. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 540\u2013550. Springer (2023)","DOI":"10.1007\/978-3-031-43898-1_52"},{"key":"6_CR24","doi-asserted-by":"crossref","unstructured":"Yang, L., Qi, L., Feng, L., Zhang, W., Shi, Y.: Revisiting weak-to-strong consistency in semi-supervised semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7236\u20137246 (2023)","DOI":"10.1109\/CVPR52729.2023.00699"},{"key":"6_CR25","doi-asserted-by":"crossref","unstructured":"Yang, L., Zhuo, W., Qi, L., Shi, Y., Gao, Y.: St++: Make self-training work better for semi-supervised semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4268\u20134277 (2022)","DOI":"10.1109\/CVPR52688.2022.00423"},{"key":"6_CR26","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"605","DOI":"10.1007\/978-3-030-32245-8_67","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2019","author":"L Yu","year":"2019","unstructured":"Yu, L., Wang, S., Li, X., Fu, C.-W., Heng, P.-A.: Uncertainty-aware self-ensembling model for semi-supervised 3d left atrium segmentation. In: Shen, D., et al. (eds.) MICCAI 2019. LNCS, vol. 11765, pp. 605\u2013613. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-32245-8_67"},{"key":"6_CR27","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Yang, J., Liu, Y., Cheng, Y., Qi, Y.: Semisam: enhancing semi-supervised medical image segmentation via sam-assisted consistency regularization. In: 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 3982\u20133986. IEEE (2024)","DOI":"10.1109\/BIBM62325.2024.10821951"},{"key":"6_CR28","unstructured":"Zou, Y., Zhang, Z., Zhang, H., Li, C.L., Bian, X., Huang, J.B., Pfister, T.: Pseudoseg: designing pseudo labels for semantic segmentation. arXiv preprint arXiv:2010.09713 (2020)"}],"container-title":["Lecture Notes in Computer Science","Skin Image Analysis, and Computer-Aided Pelvic Imaging for Female Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-05825-6_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T06:41:05Z","timestamp":1758609665000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-05825-6_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,24]]},"ISBN":["9783032058249","9783032058256"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-05825-6_6","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,24]]},"assertion":[{"value":"24 September 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DGM4MICCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"MICCAI Workshop on Deep Generative Models","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Daejeon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","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":"23 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dgm4miccai2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/dgm4miccai.github.io\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}