{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T16:29:11Z","timestamp":1778084951990,"version":"3.51.4"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031720826","type":"print"},{"value":"9783031720833","type":"electronic"}],"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\/978-3-031-72083-3_9","type":"book-chapter","created":{"date-parts":[[2024,10,13]],"date-time":"2024-10-13T18:01:42Z","timestamp":1728842502000},"page":"91-101","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Enhancing Gene Expression Prediction from\u00a0Histology Images with\u00a0Spatial Transcriptomics Completion"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4382-6390","authenticated-orcid":false,"given":"Gabriel","family":"Mejia","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6636-1173","authenticated-orcid":false,"given":"Daniela","family":"Ruiz","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0005-1185-548X","authenticated-orcid":false,"given":"Paula","family":"C\u00e1rdenas","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0008-9428-6009","authenticated-orcid":false,"given":"Leonardo","family":"Manrique","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0002-9731-7591","authenticated-orcid":false,"given":"Daniela","family":"Vega","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5244-2407","authenticated-orcid":false,"given":"Pablo","family":"Arbel\u00e1ez","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,10,14]]},"reference":[{"key":"9_CR1","doi-asserted-by":"publisher","unstructured":"Abalo, X., Thrane, K., Ji, A.L., et\u00a0al.: Human squamous cell carcinoma, visium 1 (2021). https:\/\/doi.org\/10.17632\/2bh5fchcv6.1","DOI":"10.17632\/2bh5fchcv6.1"},{"issue":"2","key":"9_CR2","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1039\/d2mo00266c","volume":"19","author":"G Av\u015far","year":"2023","unstructured":"Av\u015far, G., Pir, P.: A comparative performance evaluation of imputation methods in spatially resolved transcriptomics data. Molecular Omics 19(2), 162-173 (2023). https:\/\/doi.org\/10.1039\/d2mo00266c","journal-title":"Molecular Omics"},{"issue":"11","key":"9_CR3","doi-asserted-by":"publisher","first-page":"1352","DOI":"10.1038\/s41592-021-01264-7","volume":"18","author":"T Biancalani","year":"2021","unstructured":"Biancalani, T., Scalia, G., Buffoni, L., et\u00a0al.: Deep learning and alignment of spatially resolved single-cell transcriptomes with tangram. Nature methods 18(11), 1352\u20131362 (2021)","journal-title":"Nature methods"},{"key":"9_CR4","doi-asserted-by":"publisher","unstructured":"Chen, K.H., Boettiger, A.N., Moffitt, J.R., et\u00a0al.: Spatially resolved, highly multiplexed rna profiling in single cells. Science 348 (4 2015). https:\/\/doi.org\/10.1126\/science.aaa6090, https:\/\/www.science.org\/doi\/10.1126\/science.aaa6090","DOI":"10.1126\/science.aaa6090"},{"key":"9_CR5","unstructured":"Dosovitskiy, A., Beyer, L., Kolesnikov, A., et\u00a0al.: An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020)"},{"issue":"7922","key":"9_CR6","doi-asserted-by":"publisher","first-page":"360","DOI":"10.1038\/s41586-022-05023-2","volume":"608","author":"A Erickson","year":"2022","unstructured":"Erickson, A., He, M., Berglund, E., et\u00a0al.: Spatially resolved clonal copy number alterations in benign and malignant tissue. Nature 608(7922), 360\u2013367 (2022)","journal-title":"Nature"},{"key":"9_CR7","doi-asserted-by":"crossref","unstructured":"Fan, Y., Andrusivov\u00e1, \u017d., Wu, Y., et\u00a0al.: Expansion spatial transcriptomics. Nature Methods pp.\u00a01\u20134 (2023)","DOI":"10.1101\/2022.10.25.513696"},{"issue":"8","key":"9_CR8","doi-asserted-by":"publisher","first-page":"827","DOI":"10.1038\/s41551-020-0578-x","volume":"4","author":"B He","year":"2020","unstructured":"He, B., Bergenstr\u00e5hle, L., Stenbeck, L., et\u00a0al.: Integrating spatial gene expression and breast tumour morphology via deep learning. Nature biomedical engineering 4(8), 827\u2013834 (2020)","journal-title":"Nature biomedical engineering"},{"key":"9_CR9","doi-asserted-by":"publisher","unstructured":"He, K., Chen, X., Xie, S., Li, Y., Dollar, P., Girshick, R.: Masked autoencoders are scalable vision learners. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition 2022-June, 15979\u201315988 (11 2021). https:\/\/doi.org\/10.1109\/CVPR52688.2022.01553, https:\/\/arxiv.org\/abs\/2111.06377v3","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"9_CR10","doi-asserted-by":"publisher","unstructured":"Jiang, Y., Xie, J., Tan, X., Ye, N., Nguyen, Q.: Generalization of deep learning models for predicting spatial gene expression profiles using histology images: A breast cancer case study. bioRxiv (2023). https:\/\/doi.org\/10.1101\/2023.09.20.558624, https:\/\/www.biorxiv.org\/content\/early\/2023\/09\/22\/2023.09.20.558624","DOI":"10.1101\/2023.09.20.558624"},{"key":"9_CR11","unstructured":"Kingma, D.P., Ba, J.: Adam: A method for stochastic optimization (2017)"},{"issue":"12","key":"9_CR12","doi-asserted-by":"publisher","first-page":"1289","DOI":"10.1038\/s41592-019-0619-0","volume":"16","author":"I Korsunsky","year":"2019","unstructured":"Korsunsky, I., Millard, N., Fan, J., et\u00a0al.: Fast, sensitive and accurate integration of single-cell data with harmony. Nature methods 16(12), 1289\u20131296 (2019)","journal-title":"Nature methods"},{"key":"9_CR13","doi-asserted-by":"crossref","unstructured":"Mejia, G., C\u00e1rdenas, P., Ruiz, D., Castillo, A., Arbel\u00e1ez, P.: Sepal: Spatial gene expression prediction from local graphs. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV) Workshops. pp. 2294\u20132303 (October 2023)","DOI":"10.1109\/ICCVW60793.2023.00243"},{"issue":"1","key":"9_CR14","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1038\/s41467-023-36071-5","volume":"14","author":"R Mirzazadeh","year":"2023","unstructured":"Mirzazadeh, R., Andrusivova, Z., Larsson, L., et\u00a0al.: Spatially resolved transcriptomic profiling of degraded and challenging fresh frozen samples. Nature Communications 14(1), \u00a0509 (2023)","journal-title":"Nature Communications"},{"issue":"2","key":"9_CR15","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1038\/s41592-021-01358-2","volume":"19","author":"G Palla","year":"2022","unstructured":"Palla, G., Spitzer, H., Klein, M., et\u00a0al.: Squidpy: A scalable framework for spatial omics analysis. Nature Methods 19(2), 171-178 (Jan 2022). https:\/\/doi.org\/10.1038\/s41592-021-01358-2","journal-title":"Nature Methods"},{"key":"9_CR16","doi-asserted-by":"crossref","unstructured":"Pang, M., Su, K., Li, M.: Leveraging information in spatial transcriptomics to predict super-resolution gene expression from histology images in tumors. bioRxiv pp. 2021\u201311 (2021)","DOI":"10.1101\/2021.11.28.470212"},{"issue":"1","key":"9_CR17","first-page":"828","volume":"13","author":"SM Parigi","year":"2022","unstructured":"Parigi, S.M., Larsson, L., Das, S., et\u00a0al.: The spatial transcriptomic landscape of the healing mouse intestine following damage 13(1), \u00a0828 (2022)","journal-title":"The spatial transcriptomic landscape of the healing mouse intestine following damage"},{"key":"9_CR18","doi-asserted-by":"publisher","unstructured":"Pham, D., Tan, X., Balderson, B., et\u00a0al.: Robust mapping of spatiotemporal trajectories and cell-cell interactions in healthy and diseased tissues. Nature Communications 14(1) (Nov 2023). https:\/\/doi.org\/10.1038\/s41467-023-43120-6","DOI":"10.1038\/s41467-023-43120-6"},{"key":"9_CR19","doi-asserted-by":"publisher","unstructured":"Stickels, R.R., Murray, E., Kumar, P., et\u00a0al.: Highly sensitive spatial transcriptomics at near-cellular resolution with slide-seqv2. Nature Biotechnology 39, 313\u2013319 (3 2021). https:\/\/doi.org\/10.1038\/s41587-020-0739-1, https:\/\/www.nature.com\/articles\/s41587-020-0739-1","DOI":"10.1038\/s41587-020-0739-1"},{"issue":"7","key":"9_CR20","first-page":"1888","volume":"177","author":"T Stuart","year":"2019","unstructured":"Stuart, T., Butler, A., Hoffman, P., et\u00a0al.: Comprehensive integration of single-cell data. cell 177(7), 1888\u20131902 (2019)","journal-title":"Comprehensive integration of single-cell data. cell"},{"key":"9_CR21","doi-asserted-by":"publisher","unstructured":"St\u00e5hl, P.L., Salm\u00e9n, F., Vickovic, S., et\u00a0al.: Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 353, 78\u201382 (7 2016). https:\/\/doi.org\/10.1126\/science.aaf2403, https:\/\/www.science.org\/doi\/10.1126\/science.aaf2403","DOI":"10.1126\/science.aaf2403"},{"key":"9_CR22","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., et\u00a0al.: Attention is all you need (2023)"},{"key":"9_CR23","doi-asserted-by":"crossref","unstructured":"Vicari, M., Mirzazadeh, R., Nilsson, A., et\u00a0al.: Spatial multimodal analysis of transcriptomes and metabolomes in tissues. Nature Biotechnology pp.\u00a01\u20135 (2023)","DOI":"10.1101\/2023.01.26.525195"},{"key":"9_CR24","doi-asserted-by":"crossref","unstructured":"Villacampa, E.G., Larsson, L., Mirzazadeh, R., et\u00a0al.: Genome-wide spatial expression profiling in formalin-fixed tissues. Cell Genomics 1(3) (2021)","DOI":"10.1016\/j.xgen.2021.100065"},{"key":"9_CR25","doi-asserted-by":"publisher","unstructured":"Wang, G., Wu, S., Xiong, Z., et\u00a0al.: CROST: a comprehensive repository of spatial transcriptomics. Nucleic Acids Research 52(D1), D882\u2013D890 (10 2023). https:\/\/doi.org\/10.1093\/nar\/gkad782, https:\/\/doi.org\/10.1093\/nar\/gkad782","DOI":"10.1093\/nar\/gkad782"},{"issue":"7","key":"9_CR26","doi-asserted-by":"publisher","first-page":"1873","DOI":"10.1016\/j.cell.2019.05.006","volume":"177","author":"JD Welch","year":"2019","unstructured":"Welch, J.D., Kozareva, V., Ferreira, A., Vanderburg, C., Martin, C., Macosko, E.Z.: Single-cell multi-omic integration compares and contrasts features of brain cell identity. Cell 177(7), 1873\u20131887 (2019)","journal-title":"Cell"},{"key":"9_CR27","unstructured":"Xie, R., Pang, K., Bader, G.D., Wang, B.: Spatially resolved gene expression prediction from h &e histology images via bi-modal contrastive learning. arXiv preprint arXiv:2306.01859 (2023)"},{"key":"9_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109966","volume":"145","author":"Y Yang","year":"2024","unstructured":"Yang, Y., Hossain, M.Z., Stone, E., Rahman, S.: Spatial transcriptomics analysis of gene expression prediction using exemplar guided graph neural network. Pattern Recognition 145, 109966 (2024)","journal-title":"Pattern Recognition"},{"key":"9_CR29","doi-asserted-by":"crossref","unstructured":"Yang, Y., Hossain, M.Z., Stone, E.A., Rahman, S.: Exemplar guided deep neural network for spatial transcriptomics analysis of gene expression prediction. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision. pp. 5039\u20135048 (2023)","DOI":"10.1109\/WACV56688.2023.00501"},{"key":"9_CR30","doi-asserted-by":"crossref","unstructured":"Zeng, Y., Wei, Z., Yu, W., et\u00a0al.: Spatial transcriptomics prediction from histology jointly through transformer and graph neural networks. Briefings in Bioinformatics 23(5), bbac297 (2022)","DOI":"10.1093\/bib\/bbac297"},{"key":"9_CR31","doi-asserted-by":"crossref","unstructured":"Zhang, X., Zhou, X., Lin, M., Sun, J.: Shufflenet: An extremely efficient convolutional neural network for mobile devices. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 6848\u20136856 (2018)","DOI":"10.1109\/CVPR.2018.00716"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72083-3_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,13]],"date-time":"2024-10-13T18:03:28Z","timestamp":1728842608000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72083-3_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031720826","9783031720833"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72083-3_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"14 October 2024","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":"MICCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Medical Image Computing and Computer-Assisted Intervention","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Marrakesh","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Morocco","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":"7 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conferences.miccai.org\/2024\/en\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}