{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T23:20:19Z","timestamp":1772839219146,"version":"3.50.1"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031366154","type":"print"},{"value":"9783031366161","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-36616-1_48","type":"book-chapter","created":{"date-parts":[[2023,6,24]],"date-time":"2023-06-24T18:03:41Z","timestamp":1687629821000},"page":"603-614","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Automated Orientation Detection of\u00a03D Head Reconstructions from\u00a0sMRI Using Multiview Orthographic Projections: An Image Classification-Based Approach"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6325-8744","authenticated-orcid":false,"given":"\u00c1lvaro","family":"Heredia-Lid\u00f3n","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3644-491X","authenticated-orcid":false,"given":"Alejandro","family":"Gonz\u00e1lez","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8265-3651","authenticated-orcid":false,"given":"Carlos","family":"Guerrero-Mosquera","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7330-9621","authenticated-orcid":false,"given":"Rub\u00e8n","family":"Gonz\u00e0lez-Colom","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9799-0252","authenticated-orcid":false,"given":"Luis M.","family":"Echeverry","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6522-3999","authenticated-orcid":false,"given":"Noem\u00ed","family":"Hostalet","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5557-1562","authenticated-orcid":false,"given":"Raymond","family":"Salvador","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8159-8563","authenticated-orcid":false,"given":"Edith","family":"Pomarol-Clotet","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1340-638X","authenticated-orcid":false,"given":"Juan","family":"Fortea","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3061-2123","authenticated-orcid":false,"given":"Neus","family":"Mart\u00ednez-Abad\u00edas","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9963-6241","authenticated-orcid":false,"given":"Mar","family":"Fatj\u00f3-Vilas","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6209-3033","authenticated-orcid":false,"given":"Xavier","family":"Sevillano","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,6,25]]},"reference":[{"key":"48_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1096\/fasebj.2020.34.s1.05095","volume":"34","author":"N Mart\u00ednez-Abad\u00edas","year":"2020","unstructured":"Mart\u00ednez-Abad\u00edas, N., et al.: Understanding brain\/face integration from neuropsychiatric disorders. FASEB J. 34, 1\u20131 (2020). https:\/\/doi.org\/10.1096\/fasebj.2020.34.s1.05095","journal-title":"FASEB J."},{"key":"48_CR2","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1186\/s13034-017-0195-y","volume":"11","author":"L Myers","year":"2017","unstructured":"Myers, L., et al.: Minor physical anomalies in neurodevelopmental disorders: a twin study. Child Adolesc. Psychiatry Ment. Health 11, 57 (2017). https:\/\/doi.org\/10.1186\/s13034-017-0195-y","journal-title":"Child Adolesc. Psychiatry Ment. Health"},{"key":"48_CR3","doi-asserted-by":"publisher","first-page":"817","DOI":"10.1002\/humu.22054","volume":"33","author":"P Hammond","year":"2012","unstructured":"Hammond, P., Suttie, M.: Large-scale objective phenotyping of 3D facial morphology. Hum. Mutat. 33, 817\u2013825 (2012). https:\/\/doi.org\/10.1002\/humu.22054","journal-title":"Hum. Mutat."},{"key":"48_CR4","doi-asserted-by":"publisher","first-page":"607","DOI":"10.1111\/joa.12576","volume":"230","author":"M Li","year":"2017","unstructured":"Li, M., et al.: Rapid automated landmarking for morphometric analysis of three-dimensional facial scans. J. Anat. 230, 607\u2013618 (2017). https:\/\/doi.org\/10.1111\/joa.12576","journal-title":"J. Anat."},{"key":"48_CR5","doi-asserted-by":"publisher","first-page":"1682","DOI":"10.1038\/s41436-020-0845-y","volume":"22","author":"B Hallgr\u00edmsson","year":"2020","unstructured":"Hallgr\u00edmsson, B., et al.: Automated syndrome diagnosis by three-dimensional facial imaging. Genet. Med. 22, 1682\u20131693 (2020). https:\/\/doi.org\/10.1038\/s41436-020-0845-y","journal-title":"Genet. Med."},{"key":"48_CR6","doi-asserted-by":"publisher","first-page":"1510","DOI":"10.1038\/nn.3818","volume":"17","author":"RA Poldrack","year":"2014","unstructured":"Poldrack, R.A., Gorgolewski, K.J.: Making big data open: data sharing in neuroimaging. Nat. Neurosci. 17, 1510\u20131517 (2014). https:\/\/doi.org\/10.1038\/nn.3818","journal-title":"Nat. Neurosci."},{"key":"48_CR7","doi-asserted-by":"publisher","first-page":"108591","DOI":"10.1016\/j.patcog.2022.108591","volume":"127","author":"A Abate","year":"2022","unstructured":"Abate, A., Bisogni, C., Castiglione, A., Nappi, M.: Head pose estimation: an extensive survey on recent techniques and applications. Pattern Recognit. 127, 108591 (2022). https:\/\/doi.org\/10.1016\/j.patcog.2022.108591","journal-title":"Pattern Recognit."},{"key":"48_CR8","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1016\/j.vrih.2020.05.002","volume":"2","author":"Z Zhang","year":"2020","unstructured":"Zhang, Z., Dai, Y., Sun, J.: Deep learning based point cloud registration: an overview. Virtual Reality Intell. Hardw. 2, 222\u2013246 (2020). https:\/\/doi.org\/10.1016\/j.vrih.2020.05.002","journal-title":"Virtual Reality Intell. Hardw."},{"key":"48_CR9","doi-asserted-by":"publisher","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.90","DOI":"10.1109\/CVPR.2016.90"},{"issue":"8","key":"48_CR10","doi-asserted-by":"publisher","first-page":"1737","DOI":"10.1109\/TMI.2018.2798801","volume":"37","author":"B Hou","year":"2018","unstructured":"Hou, B., et al.: 3-D reconstruction in canonical co-ordinate space from arbitrarily oriented 2-D images. IEEE Trans. Med. Imaging 37(8), 1737\u20131750 (2018). https:\/\/doi.org\/10.1109\/TMI.2018.2798801","journal-title":"IEEE Trans. Med. Imaging"},{"key":"48_CR11","doi-asserted-by":"publisher","unstructured":"Namburete, A.I.L. et al.: Fully-automated alignment of 3D fetal brain ultrasound to a canonical reference space using multi-task learning. Med. Image Anal. 46, 1\u201314 (2018). https:\/\/doi.org\/10.1016\/j.media.2018.02.006","DOI":"10.1016\/j.media.2018.02.006"},{"key":"48_CR12","doi-asserted-by":"publisher","unstructured":"Hezroni I., Drory, A., Giryes, R., Avidan S.: DeepBBS: deep best buddies for point cloud registration. In: 2021 International Conference on 3D Vision (3DV), London, United Kingdom, pp. 342\u2013351 (2021). https:\/\/doi.org\/10.1109\/3DV53792.2021.00044","DOI":"10.1109\/3DV53792.2021.00044"},{"key":"48_CR13","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1109\/34.121791","volume":"14","author":"PJ Besl","year":"1992","unstructured":"Besl, P.J., McKay, N.D.: A method for registration of 3-D shapes. IEEE Trans. Pattern Anal. Mach. Intell. 14, 239\u2013256 (1992). https:\/\/doi.org\/10.1109\/34.121791","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"48_CR14","doi-asserted-by":"publisher","unstructured":"Aoki, Y., Goforth, H., Srivatsan, R.A., Lucey, S.: PointNetLK: robust & efficient point cloud registration using PointNet. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7156\u20137165 (2019). https:\/\/doi.org\/10.1109\/CVPR.2019.00733","DOI":"10.1109\/CVPR.2019.00733"},{"key":"48_CR15","unstructured":"Wang, Y., Solomon, J.M.: PRNet: self-supervised learning for partial-to-partial registration. In: Advances in Neural Information Processing Systems. Curran Associates, Inc. (2019)"},{"key":"48_CR16","doi-asserted-by":"publisher","unstructured":"Hempel, T., Abdelrahman, A.A., Al-Hamadi, A.: 6D rotation representation for unconstrained head pose estimation. In: 2022 IEEE International Conference on Image Processing (ICIP), pp. 2496\u20132500 (2022). https:\/\/doi.org\/10.1109\/ICIP46576.2022.9897219","DOI":"10.1109\/ICIP46576.2022.9897219"},{"key":"48_CR17","doi-asserted-by":"publisher","first-page":"108210","DOI":"10.1016\/j.patcog.2021.108210","volume":"121","author":"Y Xu","year":"2022","unstructured":"Xu, Y., Jung, C., Chang, Y.: Head pose estimation using deep neural networks and 3D point clouds. Pattern Recogn. 121, 108210 (2022). https:\/\/doi.org\/10.1016\/j.patcog.2021.108210","journal-title":"Pattern Recogn."},{"key":"48_CR18","doi-asserted-by":"publisher","unstructured":"Gomez-Donoso, F., Garcia-Garcia, A., Garcia-Rodriguez, J., Orts-Escolano, S., Cazorla, M.: LonchaNet: a sliced-based CNN architecture for real-time 3D object recognition. In: 2017 International Joint Conference on Neural Networks (IJCNN), pp. 412\u2013418 (2017). https:\/\/doi.org\/10.1109\/IJCNN.2017.7965883","DOI":"10.1109\/IJCNN.2017.7965883"},{"key":"48_CR19","doi-asserted-by":"publisher","first-page":"465","DOI":"10.1145\/356744.356750","volume":"10","author":"I Carlbom","year":"1978","unstructured":"Carlbom, I., Paciorek, J.: Planar geometric projections and viewing transformations. ACM Comput. Surv. 10, 465\u2013502 (1978). https:\/\/doi.org\/10.1145\/356744.356750","journal-title":"ACM Comput. Surv."},{"key":"48_CR20","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1145\/3065386","volume":"60","author":"A Krizhevsky","year":"2017","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. Commun. ACM 60, 84\u201390 (2017). https:\/\/doi.org\/10.1145\/3065386","journal-title":"Commun. ACM"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Image Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-36616-1_48","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,24]],"date-time":"2023-06-24T18:13:57Z","timestamp":1687630437000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-36616-1_48"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031366154","9783031366161"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-36616-1_48","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"25 June 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IbPRIA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Iberian Conference on Pattern Recognition and Image Analysis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Alicante","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 June 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 June 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ibpria2022b","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easy Chair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"86","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":"56","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":"65% - 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":"2.9","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":"2.2","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)"}}]}}