{"schema":"pith.reference-change-event.v1","doi":"10.1002/uog.6276","canonical_url":"https://pith.science/event/10.1002/uog.6276","json_url":"https://pith.science/event/10.1002/uog.6276.json","not_a_judgment":"This page records that a citing paper's bibliography includes a work with a published notice. It is not a judgment on the citing paper.","primary":{"event_id":397121,"doi":"10.1002/uog.6276","event_type":"correction","event_type_label":"Correction","source":"crossref","source_label":"Crossref","event_date":"2011-01-24","title":"Errata","work_title":"Cerebral biometry in fetal magnetic resonance imaging: new reference data","work_doi":"10.1002/uog.6276","work_arxiv_id":null,"notice_doi":"10.1002/uog.8939","flag_count":0,"flags_open":0,"flags_disputed":0,"latest_flag_at":null,"human_href":"/event/10.1002/uog.6276","json_href":"/event/10.1002/uog.6276.json"},"events":[{"event_id":397121,"doi":"10.1002/uog.6276","event_type":"correction","event_type_label":"Correction","source":"crossref","source_label":"Crossref","event_date":"2011-01-24","title":"Errata","work_title":"Cerebral biometry in fetal magnetic resonance imaging: new reference data","work_doi":"10.1002/uog.6276","work_arxiv_id":null,"notice_doi":"10.1002/uog.8939","flag_count":0,"flags_open":0,"flags_disputed":0,"latest_flag_at":null,"human_href":"/event/10.1002/uog.6276","json_href":"/event/10.1002/uog.6276.json"}],"flags":[{"id":8579,"status":"open","status_label":"Open","citing_arxiv_id":"2608.03724","citing_title":"Towards Reliable and Reproducible Fetal Brain Biometry: A Deep Learning Approach Using MRI","ref_index":47,"evidence_raw":"landmark-based fetal biometry estimation from standard ultrasound planes. arXiv:2206.14678. https://doi.org/10.48550/arXiv.2206.14678. [47] Tilea, B., Alberti, C., Adamsbaum, C., Armoogum, P., Oury, J.F., Cabrol, D., et al., 2009. Cerebral biometry in fetal magnetic resonance imaging: new reference data. Ultrasound Obstet. Gynecol. 33, 173 -81. https://doi.org/10.1002/uog.6276. Supplementary Table S1 Table S1. Mapping of the 19 tissue labels produced by BOUNTI to the 8-tissue label maps used as input for our experiments. The first column reports the combinations (∪) of BOUNTI labels (denoted as 'label_x', where x corresponds to the label index output by BOUNTI pipeline). The second column indicates the resulting label in the final label map,","evidence_cleaned":"landmark-based fetal biometry estimation from standard ultrasound planes. arXiv:2206.14678. https://doi.org/10.48550/arXiv.2206.14678. [47] Tilea, B., Alberti, C., Adamsbaum, C., Armoogum, P., Oury, J.F., Cabrol, D., et al., 2009. Cerebral biometry in fetal magnetic resonance imaging: new reference data. Ultrasound Obstet. Gynecol. 33, 173 -81. https://doi.org/10.1002/uog.6276. Supplementary Table S1 Table S1. Mapping of the 19 tissue labels produced by BOUNTI to the 8-tissue label maps used as input for our experiments. The first column reports the combinations (∪) of BOUNTI labels (denoted as 'label_x', where x corresponds to the label index output by BOUNTI pipeline). The second column indicates the resulting label in the final label map","evidence_source_label":"citation context","event_type":"correction","event_type_label":"Correction","source_label":"Crossref","event_date":"2011-01-24","work_title":"Cerebral biometry in fetal magnetic resonance imaging: new reference data","work_doi":"10.1002/uog.6276","event_doi":"10.1002/uog.6276","flag_href":"/flags/8579","event_href":"/event/10.1002/uog.6276","paper_href":"/paper/2608.03724","created_at":"2026-08-05T18:20:38.526623Z","dispute_note":null,"disputed_at":null,"disputed_by":null}],"flag_count":1,"flags_open":1,"flags_disputed":0,"desk_url":"https://pith.science/flags"}