{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T06:06:38Z","timestamp":1743141998668,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":31,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819784899"},{"type":"electronic","value":"9789819784905"}],"license":[{"start":{"date-parts":[[2024,11,7]],"date-time":"2024-11-07T00:00:00Z","timestamp":1730937600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,7]],"date-time":"2024-11-07T00:00:00Z","timestamp":1730937600000},"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\/978-981-97-8490-5_19","type":"book-chapter","created":{"date-parts":[[2024,11,6]],"date-time":"2024-11-06T09:13:21Z","timestamp":1730884401000},"page":"261-275","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SCC-CAM: Weakly Supervised Segmentation on\u00a0Brain Tumor MRI with\u00a0Similarity Constraint and\u00a0Causality"],"prefix":"10.1007","author":[{"given":"Panpan","family":"Jiao","sequence":"first","affiliation":[]},{"given":"Zhiqiang","family":"Tian","sequence":"additional","affiliation":[]},{"given":"Zhang","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Xuejian","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Zhi","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Liang","family":"Dou","sequence":"additional","affiliation":[]},{"given":"Shaoyi","family":"Du","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,7]]},"reference":[{"key":"19_CR1","doi-asserted-by":"crossref","unstructured":"Ahn, J., Kwak, S.: Learning pixel-level semantic affinity with image-level supervision for weakly supervised semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4981\u20134990 (2018)","DOI":"10.1109\/CVPR.2018.00523"},{"issue":"1","key":"19_CR2","doi-asserted-by":"publisher","first-page":"3673","DOI":"10.1038\/s41467-020-17478-w","volume":"11","author":"DC Castro","year":"2020","unstructured":"Castro, D.C., Walker, I., Glocker, B.: Causality matters in medical imaging. Nat. Commun. 11(1), 3673 (2020)","journal-title":"Nat. Commun."},{"key":"19_CR3","doi-asserted-by":"crossref","unstructured":"Chen, Z., Sun, Q.: Extracting class activation maps from non-discriminative features as well. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3135\u20133144 (2023)","DOI":"10.1109\/CVPR52729.2023.00306"},{"key":"19_CR4","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: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 248\u2013255. IEEE (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"19_CR5","doi-asserted-by":"crossref","unstructured":"Dey, R., Hong, Y.: ASC-Net: adversarial-based selective network for unsupervised anomaly segmentation. In: Medical Image Computing and Computer Assisted Intervention\u2013MICCAI 2021: 24th International Conference, Strasbourg, France, September 27\u2013October 1, 2021, Proceedings, Part V 24, pp. 236\u2013247. Springer (2021)","DOI":"10.1007\/978-3-030-87240-3_23"},{"issue":"1\u20132","key":"19_CR6","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/S0004-3702(96)00034-3","volume":"89","author":"TG Dietterich","year":"1997","unstructured":"Dietterich, T.G., Lathrop, R.H., Lozano-P\u00e9rez, T.: Solving the multiple instance problem with axis-parallel rectangles. Artif. Intell. 89(1\u20132), 31\u201371 (1997)","journal-title":"Artif. Intell."},{"key":"19_CR7","unstructured":"Dosovitskiy, A., et\u00a0al.: An image is worth $$16\\times 16$$ words: transformers for image recognition at scale. arXiv:2010.11929 (2020)"},{"key":"19_CR8","doi-asserted-by":"crossref","unstructured":"Gao, W., et al.: TS-CAM: token semantic coupled attention map for weakly supervised object localization. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 2886\u20132895 (2021)","DOI":"10.1109\/ICCV48922.2021.00288"},{"key":"19_CR9","unstructured":"Gong, C., Wang, D., Li, M., Chandra, V., Liu, Q.: Vision transformers with patch diversification. arXiv:2104.12753 (2021)"},{"key":"19_CR10","doi-asserted-by":"publisher","first-page":"5875","DOI":"10.1109\/TIP.2021.3089943","volume":"30","author":"PT Jiang","year":"2021","unstructured":"Jiang, P.T., Zhang, C.B., Hou, Q., Cheng, M.M., Wei, Y.: LayerCAM: exploring hierarchical class activation maps for localization. IEEE Trans. Image Process. 30, 5875\u20135888 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"19_CR11","doi-asserted-by":"crossref","unstructured":"Kang, H., Park, H.M., Ahn, Y., Van\u00a0Messem, A., De\u00a0Neve, W.: Towards a quantitative analysis of class activation mapping for deep learning-based computer-aided diagnosis. In: Medical Imaging 2021: Image Perception, Observer Performance, and Technology Assessment, vol. 11599, pp. 119\u2013131. SPIE (2021)","DOI":"10.1117\/12.2580819"},{"key":"19_CR12","doi-asserted-by":"crossref","unstructured":"Kolesnikov, A., Lampert, C.H.: Seed, expand and constrain: three principles for weakly-supervised image segmentation. In: Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11\u201314, 2016, Proceedings, Part IV 14, pp. 695\u2013711. Springer (2016)","DOI":"10.1007\/978-3-319-46493-0_42"},{"key":"19_CR13","doi-asserted-by":"crossref","unstructured":"Kweon, H., Yoon, S.H., Yoon, K.J.: Weakly supervised semantic segmentation via adversarial learning of classifier and reconstructor. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11329\u201311339 (2023)","DOI":"10.1109\/CVPR52729.2023.01090"},{"key":"19_CR14","doi-asserted-by":"crossref","unstructured":"Lee, K.H., Park, C., Oh, J., Kwak, N.: LFI-CAM: learning feature importance for better visual explanation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1355\u20131363 (2021)","DOI":"10.1109\/ICCV48922.2021.00139"},{"key":"19_CR15","unstructured":"Loshchilov, I., Hutter, F.: Decoupled weight decay regularization. arXiv:1711.05101 (2017)"},{"key":"19_CR16","doi-asserted-by":"crossref","unstructured":"Muhammad, M.B., Yeasin, M.: Eigen-CAM: class activation map using principal components. In: 2020 International Joint Conference on Neural Networks (IJCNN), pp.\u00a01\u20137. IEEE (2020)","DOI":"10.1109\/IJCNN48605.2020.9206626"},{"key":"19_CR17","doi-asserted-by":"crossref","unstructured":"Nie, W., Zhang, C., Song, D., Bai, Y., Xie, K., Liu, A.A.: Chest X-ray image classification: a causal perspective. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 25\u201335. Springer (2023)","DOI":"10.1007\/978-3-031-43898-1_3"},{"issue":"4","key":"19_CR18","doi-asserted-by":"publisher","first-page":"1095","DOI":"10.1109\/TMI.2022.3224067","volume":"42","author":"C Ouyang","year":"2022","unstructured":"Ouyang, C., Chen, C., Li, S., Li, Z., Qin, C., Bai, W., Rueckert, D.: Causality-inspired single-source domain generalization for medical image segmentation. IEEE Trans. Med. Imaging 42(4), 1095\u20131106 (2022)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"19_CR19","unstructured":"Pearl, J., Glymour, M., Jewell, N.P.: Causal Inference in Statistics: A Primer. Wiley (2016)"},{"key":"19_CR20","unstructured":"Pearl, J., et al.: Models, reasoning and inference. Cambridge University Press, Cambridge, UK 19(2), 3 (2000)"},{"key":"19_CR21","doi-asserted-by":"crossref","unstructured":"Qian, Z., Li, K., Lai, M., Chang, E.I.C., Wei, B., Fan, Y., Xu, Y.: Transformer based multiple instance learning for weakly supervised histopathology image segmentation. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 160\u2013170. Springer (2022)","DOI":"10.1007\/978-3-031-16434-7_16"},{"key":"19_CR22","unstructured":"Ramaswamy, H.G., et\u00a0al.: Ablation-CAM: visual explanations for deep convolutional network via gradient-free localization. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 983\u2013991 (2020)"},{"key":"19_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"},{"key":"19_CR24","doi-asserted-by":"crossref","unstructured":"Sui, Y., Wang, X., Wu, J., Lin, M., He, X., Chua, T.S.: Causal attention for interpretable and generalizable graph classification. In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 1696\u20131705 (2022)","DOI":"10.1145\/3534678.3539366"},{"key":"19_CR25","unstructured":"Touvron, H., Cord, M., Douze, M., Massa, F., Sablayrolles, A., J\u00e9gou, H.: Training data-efficient image transformers & distillation through attention. In: International Conference on Machine Learning, pp. 10347\u201310357. PMLR (2021)"},{"key":"19_CR26","unstructured":"Vaswani, A., et al.: Attention is all you need. Adv. Neural Inf. Process. Syst. 30 (2017)"},{"key":"19_CR27","doi-asserted-by":"crossref","unstructured":"Wang, H., et al.: Score-CAM: score-weighted visual explanations for convolutional neural networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 24\u201325 (2020)","DOI":"10.1109\/CVPRW50498.2020.00020"},{"key":"19_CR28","doi-asserted-by":"crossref","unstructured":"Wang, T., Huang, J., Zhang, H., Sun, Q.: Visual commonsense R-CNN. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10760\u201310770 (2020)","DOI":"10.1109\/CVPR42600.2020.01077"},{"key":"19_CR29","doi-asserted-by":"crossref","unstructured":"Xu, L., Ouyang, W., Bennamoun, M., Boussaid, F., Xu, D.: Multi-class token transformer for weakly supervised semantic segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4310\u20134319 (2022)","DOI":"10.1109\/CVPR52688.2022.00427"},{"key":"19_CR30","first-page":"655","volume":"33","author":"D Zhang","year":"2020","unstructured":"Zhang, D., Zhang, H., Tang, J., Hua, X.S., Sun, Q.: Causal intervention for weakly-supervised semantic segmentation. Adv. Neural. Inf. Process. Syst. 33, 655\u2013666 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"19_CR31","doi-asserted-by":"crossref","unstructured":"Zhou, B., Khosla, A., Lapedriza, A., Oliva, A., Torralba, A.: Learning deep features for discriminative localization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2921\u20132929 (2016)","DOI":"10.1109\/CVPR.2016.319"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-8490-5_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,6]],"date-time":"2024-11-06T09:14:47Z","timestamp":1730884487000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-8490-5_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,7]]},"ISBN":["9789819784899","9789819784905"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-8490-5_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,11,7]]},"assertion":[{"value":"7 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Urumqi","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":"18 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2024.prcv.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}