{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,20]],"date-time":"2025-09-20T22:06:19Z","timestamp":1758405979983,"version":"3.40.3"},"publisher-location":"Cham","reference-count":30,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031733895"},{"type":"electronic","value":"9783031733901"}],"license":[{"start":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T00:00:00Z","timestamp":1730332800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T00:00:00Z","timestamp":1730332800000},"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\/978-3-031-73390-1_16","type":"book-chapter","created":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T16:24:01Z","timestamp":1730305441000},"page":"267-283","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["SparseSSP: 3D Subcellular Structure Prediction from\u00a0Sparse-View Transmitted Light Images"],"prefix":"10.1007","author":[{"given":"Jintu","family":"Zheng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qizhe","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuehui","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zenan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,10,31]]},"reference":[{"issue":"2","key":"16_CR1","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1038\/s41580-019-0173-8","volume":"21","author":"FJ Bock","year":"2020","unstructured":"Bock, F.J., Tait, S.W.: Mitochondria as multifaceted regulators of cell death. Nat. Rev. Mol. Cell Biol. 21(2), 85\u2013100 (2020)","journal-title":"Nat. Rev. Mol. Cell Biol."},{"issue":"3","key":"16_CR2","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1038\/s41580-019-0208-1","volume":"21","author":"JG Carlton","year":"2020","unstructured":"Carlton, J.G., Jones, H., Eggert, U.S.: Membrane and organelle dynamics during cell division. Nat. Rev. Mol. Cell Biol. 21(3), 151\u2013166 (2020)","journal-title":"Nat. Rev. Mol. Cell Biol."},{"issue":"6208","key":"16_CR3","doi-asserted-by":"publisher","first-page":"1257998","DOI":"10.1126\/science.1257998","volume":"346","author":"BC Chen","year":"2014","unstructured":"Chen, B.C., et al.: Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution. Science 346(6208), 1257998 (2014)","journal-title":"Science"},{"key":"16_CR4","doi-asserted-by":"crossref","unstructured":"Cheng, S., et al.: Single-cell cytometry via multiplexed fluorescence prediction by label-free reflectance microscopy. Science advances 7(3), eabe0431 (2021)","DOI":"10.1126\/sciadv.abe0431"},{"issue":"1","key":"16_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s43586-021-00029-y","volume":"1","author":"JA Christopher","year":"2021","unstructured":"Christopher, J.A., et al.: Subcellular proteomics. Nature Rev. Methods Primers 1(1), 1\u201324 (2021)","journal-title":"Nature Rev. Methods Primers"},{"key":"16_CR6","doi-asserted-by":"crossref","unstructured":"Dmitriev, K., Kaufman, A.E.: Learning multi-class segmentations from single-class datasets. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9501\u20139511 (2019)","DOI":"10.1109\/CVPR.2019.00973"},{"issue":"5","key":"16_CR7","doi-asserted-by":"publisher","first-page":"1430","DOI":"10.1016\/j.cell.2018.09.057","volume":"175","author":"Y Guo","year":"2018","unstructured":"Guo, Y., et al.: Visualizing intracellular organelle and cytoskeletal interactions at nanoscale resolution on millisecond timescales. Cell 175(5), 1430\u20131442 (2018)","journal-title":"Cell"},{"key":"16_CR8","doi-asserted-by":"crossref","unstructured":"Gut, G., Herrmann, M.D., Pelkmans, L.: Multiplexed protein maps link subcellular organization to cellular states. Science 361(6401), eaar7042 (2018)","DOI":"10.1126\/science.aar7042"},{"issue":"6","key":"16_CR9","doi-asserted-by":"publisher","first-page":"1418","DOI":"10.1109\/TMI.2018.2823768","volume":"37","author":"Y Han","year":"2018","unstructured":"Han, Y., Ye, J.C.: Framing u-net via deep convolutional framelets: Application to sparse-view ct. IEEE Trans. Med. Imaging 37(6), 1418\u20131429 (2018)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"1","key":"16_CR10","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1109\/TRPMS.2020.3011413","volume":"5","author":"D Hu","year":"2020","unstructured":"Hu, D., et al.: Hybrid-domain neural network processing for sparse-view ct reconstruction. IEEE Tran. Radiation Plasma Med. Sci. 5(1), 88\u201398 (2020)","journal-title":"IEEE Tran. Radiation Plasma Med. Sci."},{"issue":"8","key":"16_CR11","doi-asserted-by":"publisher","first-page":"1700003","DOI":"10.1002\/bies.201700003","volume":"39","author":"J Icha","year":"2017","unstructured":"Icha, J., Weber, M., Waters, J.C., Norden, C.: Phototoxicity in live fluorescence microscopy, and how to avoid it. BioEssays 39(8), 1700003 (2017)","journal-title":"BioEssays"},{"key":"16_CR12","doi-asserted-by":"crossref","unstructured":"Im, K., Mareninov, S., Diaz, M., Yong, W.H.: An introduction to performing immunofluorescence staining. Biobanking, pp. 299\u2013311 (2019)","DOI":"10.1007\/978-1-4939-8935-5_26"},{"issue":"12","key":"16_CR13","doi-asserted-by":"publisher","first-page":"1329","DOI":"10.1038\/s41556-021-00802-x","volume":"23","author":"Y Jo","year":"2021","unstructured":"Jo, Y., Cho, H., Park, W.S., Kim, G., Ryu, D., Kim, Y.S., Lee, M., Park, S., Lee, M.J., Joo, H., et al.: Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning. Nat. Cell Biol. 23(12), 1329\u20131337 (2021)","journal-title":"Nat. Cell Biol."},{"issue":"1","key":"16_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41467-020-20062-x","volume":"11","author":"ME Kandel","year":"2020","unstructured":"Kandel, M.E., et al.: Phase imaging with computational specificity (pics) for measuring dry mass changes in sub-cellular compartments. Nat. Commun. 11(1), 1\u201310 (2020)","journal-title":"Nat. Commun."},{"issue":"2","key":"16_CR15","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1109\/TRPMS.2018.2867611","volume":"3","author":"H Lee","year":"2018","unstructured":"Lee, H., Lee, J., Kim, H., Cho, B., Cho, S.: Deep-neural-network-based sinogram synthesis for sparse-view ct image reconstruction. IEEE Trans. Radiation Plasma Med. Sci. 3(2), 109\u2013119 (2018)","journal-title":"IEEE Trans. Radiation Plasma Med. Sci."},{"key":"16_CR16","doi-asserted-by":"crossref","unstructured":"Li, Z., Ma, C., Chen, J., Zhang, J., Shan, H.: Learning to distill global representation for sparse-view ct. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 21196\u201321207 (2023)","DOI":"10.1109\/ICCV51070.2023.01938"},{"issue":"23","key":"16_CR17","doi-asserted-by":"publisher","first-page":"4868","DOI":"10.3390\/math11234868","volume":"11","author":"P Liu","year":"2023","unstructured":"Liu, P., Gu, C., Wu, B., Liao, X., Qian, Y., Chen, G.: 3d multi-organ and tumor segmentation based on re-parameterize diverse experts. Mathematics 11(23), 4868 (2023)","journal-title":"Mathematics"},{"key":"16_CR18","doi-asserted-by":"crossref","unstructured":"Mescheder, L.M., Oechsle, M., Niemeyer, M., Nowozin, S., Geiger, A.: Occupancy networks: Learning 3d reconstruction in function space. CoRR abs\/1812.03828 (2018). http:\/\/arxiv.org\/abs\/1812.03828","DOI":"10.1109\/CVPR.2019.00459"},{"key":"16_CR19","doi-asserted-by":"crossref","unstructured":"Min, C., Xiao, L., Zhao, D., Nie, Y., Dai, B.: Uniscene: Multi-camera unified pre-training via 3d scene reconstruction (2024)","DOI":"10.1109\/LRA.2024.3362635"},{"issue":"11","key":"16_CR20","doi-asserted-by":"publisher","first-page":"917","DOI":"10.1038\/s41592-018-0111-2","volume":"15","author":"C Ounkomol","year":"2018","unstructured":"Ounkomol, C., Seshamani, S., Maleckar, M.M., Collman, F., Johnson, G.R.: Label-free prediction of three-dimensional fluorescence images from transmitted-light microscopy. Nat. Methods 15(11), 917\u2013920 (2018)","journal-title":"Nat. Methods"},{"key":"16_CR21","doi-asserted-by":"crossref","unstructured":"Shi, W., et al.: Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1874\u20131883 (2016)","DOI":"10.1109\/CVPR.2016.207"},{"issue":"11","key":"16_CR22","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1038\/nbt.3713","volume":"34","author":"S Skylaki","year":"2016","unstructured":"Skylaki, S., Hilsenbeck, O., Schroeder, T.: Challenges in long-term imaging and quantification of single-cell dynamics. Nat. Biotechnol. 34(11), 1137\u20131144 (2016)","journal-title":"Nat. Biotechnol."},{"key":"16_CR23","doi-asserted-by":"crossref","unstructured":"Sun, G., et al.: Task switching network for multi-task learning. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 8291\u20138300 (2021)","DOI":"10.1109\/ICCV48922.2021.00818"},{"key":"16_CR24","unstructured":"Thul, P.J., et\u00a0al.: A subcellular map of the human proteome. Science 356(6340), eaal3321 (2017)"},{"issue":"6509","key":"16_CR25","doi-asserted-by":"publisher","first-page":"1395","DOI":"10.1126\/science.abd3629","volume":"369","author":"G Wolff","year":"2020","unstructured":"Wolff, G., et al.: A molecular pore spans the double membrane of the coronavirus replication organelle. Science 369(6509), 1395\u20131398 (2020)","journal-title":"Science"},{"key":"16_CR26","doi-asserted-by":"crossref","unstructured":"Wu, H., Pang, S., Sowmya, A.: Tgnet: A task-guided network architecture for multi-organ and tumour segmentation from partially labelled datasets. In: 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), pp.\u00a01\u20135. IEEE (2022)","DOI":"10.1109\/ISBI52829.2022.9761582"},{"key":"16_CR27","unstructured":"Yu, Z., et al.: Flashocc: fast and memory-efficient occupancy prediction via channel-to-height plugin. arXiv preprint arXiv:2311.12058 (2023)"},{"key":"16_CR28","doi-asserted-by":"crossref","unstructured":"Zhang, J., Xie, Y., Xia, Y., Shen, C.: Dodnet: learning to segment multi-organ and tumors from multiple partially labeled datasets. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1195\u20131204 (2021)","DOI":"10.1109\/CVPR46437.2021.00125"},{"issue":"6","key":"16_CR29","doi-asserted-by":"publisher","first-page":"1407","DOI":"10.1109\/TMI.2018.2823338","volume":"37","author":"Z Zhang","year":"2018","unstructured":"Zhang, Z., Liang, X., Dong, X., Xie, Y., Cao, G.: A sparse-view ct reconstruction method based on combination of densenet and deconvolution. IEEE Trans. Med. Imaging 37(6), 1407\u20131417 (2018)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"16_CR30","doi-asserted-by":"crossref","unstructured":"Zhou, D., et al.: Repmode: learning to re-parameterize diverse experts for subcellular structure prediction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3312\u20133322 (2023)","DOI":"10.1109\/CVPR52729.2023.00323"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-73390-1_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T16:35:43Z","timestamp":1730306143000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-73390-1_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,31]]},"ISBN":["9783031733895","9783031733901"],"references-count":30,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-73390-1_16","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,10,31]]},"assertion":[{"value":"31 October 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Milan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","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":"29 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2024.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}