{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T15:08:34Z","timestamp":1764688114726,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":27,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819755875"},{"type":"electronic","value":"9789819755882"}],"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\/978-981-97-5588-2_25","type":"book-chapter","created":{"date-parts":[[2024,8,12]],"date-time":"2024-08-12T18:02:48Z","timestamp":1723485768000},"page":"290-301","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["BGMA-Net: A Boundary-Guided and Multi-attention Network for Skin Lesion Segmentation"],"prefix":"10.1007","author":[{"given":"Cong","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yao","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuan","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haitao","family":"Gan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,8,13]]},"reference":[{"key":"25_CR1","doi-asserted-by":"publisher","unstructured":"Ge, Z., Demyanov, S., Chakravorty, R., Bowling, A., Garnavi, R.: Skin disease recognition using deep saliency features and multimodal learning of dermoscopy and clinical images. In: Descoteaux, M., Maier-Hein, L., Franz, A., Jannin, P., Collins, D., Duchesne, S. (eds.) Medical Image Computing and Computer Assisted Intervention - MICCAI 2017. MICCAI 2017. LNCS(), vol. 10435. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-66179-7_29","DOI":"10.1007\/978-3-319-66179-7_29"},{"issue":"1","key":"25_CR2","doi-asserted-by":"publisher","first-page":"7","DOI":"10.3322\/caac.21551","volume":"69","author":"RL Siegel","year":"2019","unstructured":"Siegel, R.L., Miller, K.D., Jemal, A.: Cancer statistics, 2019. CA Cancer J. Clin. 69(1), 7\u201334 (2019)","journal-title":"CA Cancer J. Clin."},{"key":"25_CR3","doi-asserted-by":"publisher","unstructured":"Wu, C., Zhang, H., Chen, D., Gan, H.: A multi-scale and multi-attention network for skin lesion segmentation. In: Luo, B., Cheng, L., Wu, Z.G., Li, H., Li, C. (eds.) Neural Information Processing. ICONIP 2023. LNCS, vol. 14450. Springer, Singapore (2024) https:\/\/doi.org\/10.1007\/978-981-99-8070-3_41","DOI":"10.1007\/978-981-99-8070-3_41"},{"key":"25_CR4","doi-asserted-by":"crossref","unstructured":"Wang, L., Wong, L., You, Z.H., Huang, D.: AMDECDA: attention mechanism combined with data ensemble strategy for predicting circRNA-disease association. IEEE Trans. Big Data 10, 320\u2013329 (2023)","DOI":"10.1109\/TBDATA.2023.3334673"},{"key":"25_CR5","doi-asserted-by":"crossref","unstructured":"Wu, C., Zou, Y., Zhan, J.: DA-U-Net: densely connected convolutional networks and decoder with attention gate for retinal vessel segmentation. In: IOP Conference Series: Materials Science and Engineering. vol. 533. IOP Publishing (2019)","DOI":"10.1088\/1757-899X\/533\/1\/012053"},{"issue":"11","key":"25_CR6","doi-asserted-by":"publisher","first-page":"3217","DOI":"10.1007\/s11517-022-02663-4","volume":"60","author":"C Wu","year":"2022","unstructured":"Wu, C., Li, S., Liu, X., Jiang, F., Shi, B.: DMs-MAFM+EfficientNet: a hybrid model for predicting dysthyroid optic neuropathy. Med. Biol. Eng. Compu. 60(11), 3217\u20133230 (2022)","journal-title":"Med. Biol. Eng. Compu."},{"key":"25_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.106274","volume":"151","author":"C Wu","year":"2022","unstructured":"Wu, C., Long, C., Li, S., Yang, J., Jiang, F., Zhou, R.: MSRAformer: multiscale spatial reverse attention network for polyp segmentation. Comput. Biol. Med. 151, 106274 (2022)","journal-title":"Comput. Biol. Med."},{"key":"25_CR8","doi-asserted-by":"crossref","unstructured":"Wu, C., Zou, Y., Yang, Z.: U-GAN: generative Adversarial Networks with U-Net for Retinal Vessel Segmentation. In: 14th International Conference on Computer Science & Education, pp. 642\u2013646 (2019)","DOI":"10.1109\/ICCSE.2019.8845397"},{"key":"25_CR9","doi-asserted-by":"publisher","first-page":"670","DOI":"10.1016\/j.compmedimag.2008.08.003","volume":"32","author":"ME Celebi","year":"2008","unstructured":"Celebi, M.E., et al.: Automatic detection of blue-white veil and related structures in dermoscopy images. Comput. Med. Imaging Graph. 32, 670\u2013677 (2008)","journal-title":"Comput. Med. Imaging Graph."},{"key":"25_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.106462","volume":"155","author":"S Qiu","year":"2023","unstructured":"Qiu, S., Li, C., Feng, Y., Zuo, S., Liang, H., Xu, A.: GFANet: gated fusion attention network for skin lesion segmentation. Comput. Biol. Med. 155, 106462 (2023)","journal-title":"Comput. Biol. Med."},{"key":"25_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.108673","volume":"128","author":"H Basak","year":"2022","unstructured":"Basak, H., Kundu, R., Sarkar, R.: MFSNet: a multi focus segmentation network for skin lesion segmentation. Pattern Recognit. 128, 108673 (2022)","journal-title":"Pattern Recognit."},{"key":"25_CR12","doi-asserted-by":"publisher","unstructured":"Zhang, Z., Fu, H., Dai, H., Shen, J., Pang, Y., Shao, L.: ET-Net: a generic edge-aTtention guidance network for medical image segmentation. In: Shen, D., et al. Medical Image Computing and Computer Assisted Intervention - MICCAI 2019. MICCAI 2019. LNCS(), vol. 11764. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-32239-7_49","DOI":"10.1007\/978-3-030-32239-7_49"},{"key":"25_CR13","doi-asserted-by":"crossref","unstructured":"Zhao, J., Liu, J., Fan, D., Cao, Y., Yang, J., Cheng, M.: EGNet: Edge guidance network for salient object detection. In: ICCV 2019, pp. 8779\u20138788 (2019)","DOI":"10.1109\/ICCV.2019.00887"},{"key":"25_CR14","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Zhang, X., Peng, C., Xue, X., Sun, J.: ExFuse: Enhancing Feature Fusion for Semantic Segmentation. In: ECCV 2018, pp. 269\u2013284 (2018)","DOI":"10.1007\/978-3-030-01249-6_17"},{"key":"25_CR15","doi-asserted-by":"publisher","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W., Frangi, A. (eds) Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015. MICCAI 2015. LNCS(), vol. 9351. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"25_CR16","doi-asserted-by":"publisher","unstructured":"Zhou, Z., Rahman Siddiquee, M.M., Tajbakhsh, N., Liang, J.: UNet++: a nested u-net architecture for medical image segmentation. In: Stoyanov, D., et al. Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support. DLMIA ML-CDS 2018 2018. LNCS(), vol. 11045. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-00889-5_1","DOI":"10.1007\/978-3-030-00889-5_1"},{"key":"25_CR17","unstructured":"Oktay, O., et al.: Attention U-Net: Learning Where to Look for the Pancreas (2018). arXiv:1804.03999"},{"key":"25_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2023.107798","volume":"168","author":"R Wu","year":"2024","unstructured":"Wu, R., Lv, H., Liang, P., Cui, X., Chang, Q., Huang, X.: HSH-UNet: hybrid selective high order interactive U-shaped model for automated skin lesion segmentation. Comput. Biol. Med. 168, 107798 (2024)","journal-title":"Comput. Biol. Med."},{"key":"25_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101874","volume":"67","author":"L Mou","year":"2021","unstructured":"Mou, L., et al.: CS2-Net: deep learning segmentation of curvilinear structures in medical imaging. Med. Image Anal. 67, 101874 (2021)","journal-title":"Med. Image Anal."},{"issue":"2","key":"25_CR20","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1109\/TPAMI.2019.2938758","volume":"43","author":"S Gao","year":"2021","unstructured":"Gao, S., Cheng, M., Zhao, K., Zhang, X., Yang, M., Torr, P.: Res2Net: a new multi-scale backbone architecture. IEEE Trans. Pattern Anal. Mach. Intell. 43(2), 652\u2013662 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"3","key":"25_CR21","first-page":"2441","volume":"36","author":"H Wang","year":"2022","unstructured":"Wang, H., Cao, P., Wang, J., Zaiane, O.R.: UCTransNet: rethinking the skip connections in U-Net from a channel-wise perspective with transformer. Proc. AAAI Conf. Artif. Intell. 36(3), 2441\u20132449 (2022)","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"25_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102327","volume":"76","author":"H Wu","year":"2022","unstructured":"Wu, H., Chen, S., Chen, G., Wang, W., Lei, B., Wen, Z.: FAT-Net: feature adaptive transformers for automated skin lesion segmentation. Med. Image Anal. 76, 102327 (2022). https:\/\/doi.org\/10.1016\/j.media.2021.102327","journal-title":"Med. Image Anal."},{"issue":"7","key":"25_CR23","first-page":"11418","volume":"34","author":"X Li","year":"2020","unstructured":"Li, X., Zhao, H., Han, L., Tong, Y., Tan, S., Yang, K.: Gated fully fusion for semantic segmentation. Proc. AAAI Conf. Artif. Intell. 34(7), 11418\u201311425 (2020)","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"issue":"2","key":"25_CR24","doi-asserted-by":"publisher","first-page":"699","DOI":"10.1109\/TMI.2020.3035253","volume":"40","author":"R Gu","year":"2021","unstructured":"Gu, R., et al.: CA-Net: comprehensive attention convolutional neural networks for explainable medical image segmentation. IEEE Trans. Med. Imaging 40(2), 699\u2013711 (2021)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"10","key":"25_CR25","doi-asserted-by":"publisher","first-page":"3008","DOI":"10.1109\/TMI.2020.2983721","volume":"39","author":"S Feng","year":"2020","unstructured":"Feng, S., et al.: CPFNet: context pyramid fusion network for medical image segmentation. IEEE Trans. Med. Imaging 39(10), 3008\u20133018 (2020). https:\/\/doi.org\/10.1109\/TMI.2020.2983721","journal-title":"IEEE Trans. Med. Imaging"},{"key":"25_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102293","volume":"75","author":"D Dai","year":"2022","unstructured":"Dai, D., et al.: Ms RED: a novel multi-scale residual encoding and decoding network for skin lesion segmentation. Med. Image Anal. 75, 102293 (2022)","journal-title":"Med. Image Anal."},{"key":"25_CR27","doi-asserted-by":"crossref","unstructured":"Ruan, J., Xiang, S., Xie, M., Liu, T., Fu, Y.: MALUNet: a multi-attention and light-weight UNet for skin lesion segmentation. In: BIBM 2022, pp. 1150\u20131156. IEEE (2022)","DOI":"10.1109\/BIBM55620.2022.9995040"}],"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\/978-981-97-5588-2_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,12]],"date-time":"2024-08-12T18:06:19Z","timestamp":1723485979000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-5588-2_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819755875","9789819755882"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-5588-2_25","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":"13 August 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"}}]}}