{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T16:08:58Z","timestamp":1759334938743,"version":"build-2065373602"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030603335"},{"type":"electronic","value":"9783030603342"}],"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\/978-3-030-60334-2_11","type":"book-chapter","created":{"date-parts":[[2020,9,30]],"date-time":"2020-09-30T19:05:43Z","timestamp":1601492743000},"page":"106-115","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Augmented Reality-Based Lung Ultrasound Scanning Guidance"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3735-7700","authenticated-orcid":false,"given":"Keshav","family":"Bimbraw","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1007-0910","authenticated-orcid":false,"given":"Xihan","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0921-8298","authenticated-orcid":false,"given":"Ziming","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1314-8456","authenticated-orcid":false,"given":"Haichong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,10,1]]},"reference":[{"issue":"4","key":"11_CR1","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1007\/s001340050862","volume":"25","author":"D Lichtenstein","year":"1999","unstructured":"Lichtenstein, D., Mezi\u00e8re, G., Biderman, P., Gepner, A.: The comet-tail artifact: an ultrasound sign ruling out pneumothorax. Intensiv. Care Med. 25(4), 383\u2013388 (1999). https:\/\/doi.org\/10.1007\/s001340050862","journal-title":"Intensiv. Care Med."},{"key":"11_CR2","unstructured":"WHO: Coronavirus Disease 2019 (COVID-19) Situation Reports, 1 April 2020. WHO Situation Report 2019(72), 1\u201319. https:\/\/www.who.int\/docs\/default-source\/coronaviruse\/situation-reports\/20200324-sitrep-64-covid-19.pdf?sfvrsn=703b2c40_2%0Ahttps:\/\/www.who.int\/docs\/default-source\/coronaviruse\/situation-reports\/20200401-sitrep-72-covid-19.pdf?sfvrsn=3dd8971b_2"},{"key":"11_CR3","doi-asserted-by":"publisher","unstructured":"Soldati, G., et al.: Is there a role for lung ultrasound during the COVID-19 pandemic? J. Ultrasound Med. Off. J. Am. Inst. Ultrasound Med., 1\u20134 (2020) https:\/\/doi.org\/10.1002\/jum.15284Ads","DOI":"10.1002\/jum.15284Ads"},{"issue":"1","key":"11_CR4","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1378\/chest.07-2800","volume":"134","author":"DA Lichtenstein","year":"2008","unstructured":"Lichtenstein, D.A., Mezi\u00e8re, G.A.: Relevance of lung ultrasound in the diagnosis of acute respiratory failure the BLUE protocol. Chest 134(1), 117\u2013125 (2008). https:\/\/doi.org\/10.1378\/chest.07-2800","journal-title":"Chest"},{"key":"11_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cviu.2019.102897","volume":"192","author":"Y Chen","year":"2020","unstructured":"Chen, Y., Tian, Y., He, M.: Monocular human pose estimation: a survey of deep learning-based methods. Comput. Vis. Image Underst. 192, 1\u201323 (2020). https:\/\/doi.org\/10.1016\/j.cviu.2019.102897","journal-title":"Comput. Vis. Image Underst."},{"key":"11_CR6","doi-asserted-by":"publisher","unstructured":"Toshev, A., Szegedy, C.: DeepPose: Human pose estimation via deep neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1653\u20131660 (2014). https:\/\/doi.org\/10.1109\/CVPR.2014.214","DOI":"10.1109\/CVPR.2014.214"},{"key":"11_CR7","doi-asserted-by":"publisher","unstructured":"Carreira, J., Agrawal, P., Fragkiadaki, K., Malik, J.: Human pose estimation with iterative error feedback. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 4733\u20134742, December 2016. https:\/\/doi.org\/10.1109\/CVPR.2016.512","DOI":"10.1109\/CVPR.2016.512"},{"key":"11_CR8","doi-asserted-by":"publisher","unstructured":"Sun, C., Shrivastava, A., Singh, S., Gupta, A.: Revisiting unreasonable effectiveness of data in deep learning era. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 843\u2013852, October 2017. https:\/\/doi.org\/10.1109\/ICCV.2017.97","DOI":"10.1109\/ICCV.2017.97"},{"key":"11_CR9","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.cag.2019.09.002","volume":"85","author":"DC Luvizon","year":"2019","unstructured":"Luvizon, D.C., Tabia, H., Picard, D.: Human pose regression by combining indirect part detection and contextual information. Comput. Graph. (Pergamon) 85, 15\u201322 (2019). https:\/\/doi.org\/10.1016\/j.cag.2019.09.002","journal-title":"Comput. Graph. (Pergamon)"},{"key":"11_CR10","doi-asserted-by":"crossref","unstructured":"Fourure, D., Emonet, R., Fromont, E., Muselet, D., Tremeau, A., Wolf, C.: Residual conv-deconv grid network for semantic segmentation. In: British Machine Vision Conference, BMVC 2017 (2017). https:\/\/arxiv.org\/pdf\/1707.07958.pdf","DOI":"10.5244\/C.31.181"},{"key":"11_CR11","doi-asserted-by":"publisher","unstructured":"Sun, K., Xiao, B., Liu, D., Wang, J.: Deep high-resolution representation learning for human pose estimation. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 5686\u20135696, June 2019. https:\/\/doi.org\/10.1109\/CVPR.2019.00584","DOI":"10.1109\/CVPR.2019.00584"},{"key":"11_CR12","doi-asserted-by":"publisher","unstructured":"Tang, W., Wu, Y.: Does learning specific features for related parts help human pose estimation? In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1107\u20131116, June 2019. https:\/\/doi.org\/10.1109\/CVPR.2019.00120","DOI":"10.1109\/CVPR.2019.00120"},{"key":"11_CR13","doi-asserted-by":"publisher","unstructured":"Chen, Y., Shen, C., Wei, X.S., Liu, L., Yang, J.: Adversarial PoseNet: a structure-aware convolutional network for human pose estimation. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1221\u20131230, October 2017. https:\/\/doi.org\/10.1109\/ICCV.2017.137","DOI":"10.1109\/ICCV.2017.137"},{"key":"11_CR14","doi-asserted-by":"publisher","unstructured":"Guler, R.A., Neverova, N., Kokkinos, I.: DensePose: dense human pose estimation in the wild. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7297\u20137306 (2016). https:\/\/doi.org\/10.1109\/CVPR.2017.280","DOI":"10.1109\/CVPR.2017.280"},{"key":"11_CR15","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1016\/j.imavis.2018.05.004","volume":"76","author":"FJ Romero-Ramirez","year":"2018","unstructured":"Romero-Ramirez, F.J., Mu\u00f1oz-Salinas, R., Medina-Carnicer, R.: Speeded up detection of squared fiducial markers. Image Vis. Comput. 76, 38\u201347 (2018). https:\/\/doi.org\/10.1016\/j.imavis.2018.05.004","journal-title":"Image Vis. Comput."},{"issue":"6","key":"11_CR16","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1016\/j.ajem.2006.02.013","volume":"24","author":"G Volpicelli","year":"2006","unstructured":"Volpicelli, G., et al.: Bedside lung ultrasound in the assessment of alveolar-interstitial syndrome. Am. J. Emerg. Med. 24(6), 689\u2013696 (2006). https:\/\/doi.org\/10.1016\/j.ajem.2006.02.013","journal-title":"Am. J. Emerg. Med."},{"key":"11_CR17","doi-asserted-by":"publisher","DOI":"10.1111\/1742-6723.13546","volume-title":"CLUE: COVID-19 lung ultrasound in emergency department","author":"V Manivel","year":"2020","unstructured":"Manivel, V., Lesnewski, A., Shamim, S., Carbonatto, G., Govindan, T.: CLUE: COVID-19 lung ultrasound in emergency department. Emerg. Med. Australas., EMA (2020). https:\/\/doi.org\/10.1111\/1742-6723.13546"},{"key":"11_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.radi.2020.04.005","author":"S Moore","year":"2020","unstructured":"Moore, S., Gardiner, E.: Point of care and intensive care lung ultrasound: a reference guide for practitioners during COVID-19. Radiography (2020). https:\/\/doi.org\/10.1016\/j.radi.2020.04.005","journal-title":"Radiography"},{"issue":"2","key":"11_CR19","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1097\/ALN.0000000000000558","volume":"122","author":"B Bouhemad","year":"2015","unstructured":"Bouhemad, B., Mongodi, S., Via, G., Rouquette, I.: Ultrasound for \u201clung monitoring\u201d of ventilated patients. Anesthesiology 122(2), 437\u2013447 (2015). https:\/\/doi.org\/10.1097\/ALN.0000000000000558","journal-title":"Anesthesiology"},{"key":"11_CR20","doi-asserted-by":"publisher","unstructured":"Lee, F.C.Y.: Lung ultrasound-a primary survey of the acutely dyspneic patient. J. Intensiv. Care 4(1) (2016). https:\/\/doi.org\/10.1186\/s40560-016-0180-1","DOI":"10.1186\/s40560-016-0180-1"},{"key":"11_CR21","unstructured":"Via, G., et al.: Instrument to Respiratory Monitoring Tool, August 2012"},{"key":"11_CR22","doi-asserted-by":"publisher","unstructured":"Soldati, G., et al.: Proposal for international standardization of the use of lung ultrasound for patients with COVID-19: a simple, quantitative, reproducible method. J. Ultrasound Med. (2020). https:\/\/doi.org\/10.1002\/jum.15285","DOI":"10.1002\/jum.15285"},{"issue":"5","key":"11_CR23","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1002\/uog.22028","volume":"55","author":"F Moro","year":"2020","unstructured":"Moro, F., Buonsenso, D., et al.: How to perform lung ultrasound in pregnant women with suspected COVID-19. Ultrasound Obstet. Gynecol. Off. J. Int. Soc. Ultrasound Obstet. Gynecol. 55(5), 593\u2013598 (2020). https:\/\/doi.org\/10.1002\/uog.22028","journal-title":"Ultrasound Obstet. Gynecol. Off. J. Int. Soc. Ultrasound Obstet. Gynecol."},{"issue":"3","key":"11_CR24","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1023\/A:1022627411411","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20(3), 273\u2013297 (1995)","journal-title":"Mach. Learn."},{"key":"11_CR25","doi-asserted-by":"crossref","unstructured":"Awad, M., Khanna, R.: Support vector regression. In: Efficient learning machines, pp. 67\u201380. Apress, Berkeley (2015)","DOI":"10.1007\/978-1-4302-5990-9_4"}],"container-title":["Lecture Notes in Computer Science","Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-60334-2_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T22:53:37Z","timestamp":1759272817000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-60334-2_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030603335","9783030603342"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-60334-2_11","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":"1 October 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ASMUS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Advances in Simplifying Medical Ultrasound","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":"4 October 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"asmus2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/sites.google.com\/view\/asmus2020","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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"26","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":"9","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":"10","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":"35% - 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":"2,7","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":"2,6","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)"}}]}}