{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T01:01:36Z","timestamp":1759366896923,"version":"build-2065373602"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030597214"},{"type":"electronic","value":"9783030597221"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-59722-1_6","type":"book-chapter","created":{"date-parts":[[2020,10,2]],"date-time":"2020-10-02T17:03:01Z","timestamp":1601658181000},"page":"56-65","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Attention-Guided Quality Assessment for Automated Cryo-EM Grid Screening"],"prefix":"10.1007","author":[{"given":"Hong","family":"Xu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David E.","family":"Timm","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shireen Y.","family":"Elhabian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,9,29]]},"reference":[{"key":"6_CR1","doi-asserted-by":"publisher","unstructured":"Agard, D., Cheng, Y., Glaeser, R.M., Subramaniam, S.: Single-particle cryo-electron microscopy (Cryo-EM): progress, challenges, and perspectives for further improvement, Chap. 2. In: Advances in Imaging and Electron Physics, vol. 185, pp. 113\u2013137. Elsevier (2014). https:\/\/doi.org\/10.1016\/B978-0-12-800144-8.00002-1, http:\/\/www.sciencedirect.com\/science\/article\/pii\/B9780128001448000021","DOI":"10.1016\/B978-0-12-800144-8.00002-1"},{"key":"6_CR2","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1038\/525172a","volume":"525","author":"E Callaway","year":"2015","unstructured":"Callaway, E.: The revolution will not be crystallized: a new method sweeps through structural biology. Nature 525, 172\u2013174 (2015). https:\/\/doi.org\/10.1038\/525172a","journal-title":"Nature"},{"issue":"1","key":"6_CR3","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1042\/BST20180267","volume":"47","author":"T Ceska","year":"2019","unstructured":"Ceska, T., Chung, C.W., Cooke, R., Phillips, C., Williams, P.A.: Cryo-EM in drug discovery. Biochem. Soc. Trans. 47(1), 281\u2013293 (2019)","journal-title":"Biochem. Soc. Trans."},{"key":"6_CR4","doi-asserted-by":"publisher","first-page":"450","DOI":"10.1016\/j.cell.2015.03.049","volume":"161","author":"Y Cheng","year":"2015","unstructured":"Cheng, Y.: Single-particle Cryo-EM at crystallographic resolution. Cell 161, 450\u2013457 (2015). https:\/\/doi.org\/10.1016\/j.cell.2015.03.049","journal-title":"Cell"},{"key":"6_CR5","doi-asserted-by":"publisher","first-page":"e35383","DOI":"10.7554\/eLife.35383","volume":"7","author":"T Grant","year":"2018","unstructured":"Grant, T., Rohou, A., Grigorieff, N.: cisTEM, user-friendly software for single-particle image processing. eLife 7, e35383 (2018). https:\/\/doi.org\/10.7554\/eLife.35383","journal-title":"eLife"},{"key":"6_CR6","unstructured":"Guan, Q., Huang, Y., Zhong, Z., Zheng, Z., Zheng, L., Yang, Y.: Diagnose like a radiologist: attention guided convolutional neural network for thorax disease classification. ArXiv abs\/1801.09927 (2018)"},{"key":"6_CR7","doi-asserted-by":"publisher","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770\u2013778 (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.90","DOI":"10.1109\/CVPR.2016.90"},{"key":"6_CR8","unstructured":"Kingma, D., Rezende, D., Mohamed, S., Welling, M.: Semi-supervised learning with deep generative models. In: Advances in Neural Information Processing Systems, vol. 4 (2014)"},{"issue":"1","key":"6_CR9","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.jsb.2005.01.002","volume":"150","author":"J Lei","year":"2005","unstructured":"Lei, J., Frank, J.: Automated acquisition of cryo-electron micrographs for single particle reconstruction on an FEI Tecnai electron microscope. J. Struct. Biol. 150(1), 69\u201380 (2005). https:\/\/doi.org\/10.1016\/j.jsb.2005.01.002. http:\/\/www.sciencedirect.com\/science\/article\/pii\/S1047847705000225","journal-title":"J. Struct. Biol."},{"issue":"13","key":"6_CR10","doi-asserted-by":"publisher","first-page":"5181","DOI":"10.1074\/jbc.REV118.005602","volume":"294","author":"D Lyumkis","year":"2019","unstructured":"Lyumkis, D.: Challenges and opportunities in cryo-EM single-particle analysis. J. Biol. Chem. 294(13), 5181\u20135197 (2019). https:\/\/doi.org\/10.1074\/jbc.REV118.005602. http:\/\/www.jbc.org\/cgi\/content\/short\/REV118.005602v1","journal-title":"J. Biol. Chem."},{"key":"6_CR11","doi-asserted-by":"publisher","unstructured":"Mahendran, A., Vedaldi, A.: Understanding deep image representations by inverting them, pp. 5188\u20135196 (2015). https:\/\/doi.org\/10.1109\/CVPR.2015.7299155","DOI":"10.1109\/CVPR.2015.7299155"},{"issue":"3","key":"6_CR12","doi-asserted-by":"publisher","first-page":"290","DOI":"10.1038\/nmeth.4169","volume":"14","author":"A Punjani","year":"2017","unstructured":"Punjani, A., Rubinstein, J.L., Fleet, D.J., Brubaker, M.A.: cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination. Nat. Methods 14(3), 290\u2013296 (2017). https:\/\/doi.org\/10.1038\/nmeth.4169","journal-title":"Nat. Methods"},{"key":"6_CR13","doi-asserted-by":"publisher","unstructured":"Ranzato, M., Szummer, M.: Semi-supervised learning of compact document representations with deep networks. In: Proceedings of the 25th International Conference on Machine Learning, pp. 792\u2013799 (2008). https:\/\/doi.org\/10.1145\/1390156.1390256","DOI":"10.1145\/1390156.1390256"},{"issue":"7","key":"6_CR14","doi-asserted-by":"publisher","first-page":"471","DOI":"10.1038\/nrd.2018.77","volume":"17","author":"JP Renaud","year":"2018","unstructured":"Renaud, J.P., et al.: Cryo-EM in drug discovery: achievements, limitations and prospects. Nat. Rev. Drug Discov. 17(7), 471\u2013492 (2018)","journal-title":"Nat. Rev. Drug Discov."},{"issue":"3","key":"6_CR15","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1016\/j.jsb.2012.09.006","volume":"180","author":"SHW Scheres","year":"2012","unstructured":"Scheres, S.H.W.: RELION: implementation of a Bayesian approach to cryo-EM structure determination. J. Struct. Biol. 180(3), 519\u2013530 (2012). https:\/\/doi.org\/10.1016\/j.jsb.2012.09.006. https:\/\/pubmed.ncbi.nlm.nih.gov\/23000701, 23000701 [pmid]","journal-title":"J. Struct. Biol."},{"key":"6_CR16","unstructured":"Simonyan, K., Vedaldi, A., Zisserman, A.: Deep inside convolutional networks: visualising image classification models and saliency maps (2013, preprint)"},{"issue":"1","key":"6_CR17","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1093\/jmicro\/dfv369","volume":"65","author":"YZ Tan","year":"2015","unstructured":"Tan, Y.Z., Cheng, A., Potter, C.S., Carragher, B.: Automated data collection in single particle electron microscopy. Microscopy 65(1), 43\u201356 (2015). https:\/\/doi.org\/10.1093\/jmicro\/dfv369","journal-title":"Microscopy"},{"issue":"11","key":"6_CR18","doi-asserted-by":"publisher","first-page":"1146","DOI":"10.1038\/s41592-019-0580-y","volume":"16","author":"D Tegunov","year":"2019","unstructured":"Tegunov, D., Cramer, P.: Real-time cryo-electron microscopy data preprocessing with warp. Nat. Methods 16(11), 1146\u20131152 (2019). https:\/\/doi.org\/10.1038\/s41592-019-0580-y","journal-title":"Nat. Methods"},{"key":"6_CR19","doi-asserted-by":"publisher","unstructured":"Weston, J., Ratle, F., Collobert, R.: Deep learning via semi-supervised embedding. In: Proceedings of the 25th International Conference on Machine Learning, ICML 2008, pp. 1168\u20131175. Association for Computing Machinery, New York (2008). https:\/\/doi.org\/10.1145\/1390156.1390303","DOI":"10.1145\/1390156.1390303"},{"key":"6_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-030-01234-2_1","volume-title":"Computer Vision \u2013 ECCV 2018","author":"S Woo","year":"2018","unstructured":"Woo, S., Park, J., Lee, J.-Y., Kweon, I.S.: CBAM: convolutional block attention module. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11211, pp. 3\u201319. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01234-2_1"},{"key":"6_CR21","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"818","DOI":"10.1007\/978-3-319-10590-1_53","volume-title":"Computer Vision \u2013 ECCV 2014","author":"MD Zeiler","year":"2014","unstructured":"Zeiler, M.D., Fergus, R.: Visualizing and understanding convolutional networks. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8689, pp. 818\u2013833. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10590-1_53"},{"issue":"4","key":"6_CR22","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1038\/nmeth.4193","volume":"14","author":"SQ Zheng","year":"2017","unstructured":"Zheng, S.Q., Palovcak, E., Armache, J.P., Verba, K.A., Cheng, Y., Agard, D.A.: MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Nat. Methods 14(4), 331\u2013332 (2017). https:\/\/doi.org\/10.1038\/nmeth.4193. https:\/\/pubmed.ncbi.nlm.nih.gov\/28250466, 28250466 [pmid]","journal-title":"Nat. Methods"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2020"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-59722-1_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T22:07:48Z","timestamp":1759356468000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-59722-1_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030597214","9783030597221"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-59722-1_6","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"29 September 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"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":"Lima","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Peru","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.miccai2020.org\/en\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1809","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"542","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"30% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The conference was held virtually due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}