{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,7]],"date-time":"2026-11-07T02:26:24Z","timestamp":1794018384897,"version":"4.8.0"},"reference-count":13,"publisher":"Journal of Neurosurgery Publishing Group (JNSPG)","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,5]]},"abstract":"\n OBJECTIVE<\/jats:title>\n The authors sought to evaluate the accuracy of a novel telehealth-compatible diagnostic software system for identifying craniosynostosis within a newborn (< 1 year old) population. Agreement with gold standard craniometric diagnostics was also assessed.<\/jats:p>\n <\/jats:sec>\n \n METHODS<\/jats:title>\n Cranial shape classification software accuracy was compared to that of blinded craniofacial specialists using a data set of open-source (n = 40) and retrospectively collected newborn orthogonal top-down cranial images, with or without additional facial views (n = 339), culled between April 1, 2008, and February 29, 2020. Based on image quality, midface visibility, and visibility of the cranial equator, 351 image sets were deemed acceptable. Accuracy, sensitivity, and specificity were calculated for the software versus specialist classification. Software agreement with optical craniometrics was assessed with intraclass correlation coefficients.<\/jats:p>\n <\/jats:sec>\n \n RESULTS<\/jats:title>\n The cranial shape classification software had an accuracy of 93.3% (95% CI 86.8\u201398.8; p < 0.001), with a sensitivity of 92.0% and specificity of 94.3%. Intraclass correlation coefficients for measurements of the cephalic index and cranial vault asymmetry index compared to optical measurements were 0.95 (95% CI 0.84\u20130.98; p < 0.001) and 0.67 (95% CI 0.24\u20130.88; p = 0.003), respectively.<\/jats:p>\n <\/jats:sec>\n \n CONCLUSIONS<\/jats:title>\n These results support the use of image processing\u2013based neonatal cranial deformity classification software for remote screening of nonsyndromic craniosynostosis in a newborn population and as a substitute for optical scanner\u2013 or CT-based craniometrics. This work has implications that suggest the potential for the development of software for a mobile platform that would allow for screening by telemedicine or in a primary care setting.<\/jats:p>\n <\/jats:sec>","DOI":"10.3171\/2020.9.peds20605","type":"journal-article","created":{"date-parts":[[2021,3,19]],"date-time":"2021-03-19T03:09:38Z","timestamp":1616123378000},"page":"581-588","source":"Crossref","is-referenced-by-count":30,"title":["Image processing and machine learning for telehealth craniosynostosis screening in newborns"],"prefix":"10.3171","volume":"27","author":[{"given":"Markus J.","family":"Bookland","sequence":"first","affiliation":[{"name":"Division of Neurosurgery, Connecticut Children\u2019s, Hartford;"},{"name":"Department of Surgery, University of Connecticut Health Center, Farmington, Connecticut; and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edward S.","family":"Ahn","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Mayo Clinic, Rochester, Minnesota"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Petronella","family":"Stoltz","sequence":"additional","affiliation":[{"name":"Division of Neurosurgery, Connecticut Children\u2019s, Hartford;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonathan E.","family":"Martin","sequence":"additional","affiliation":[{"name":"Division of Neurosurgery, Connecticut Children\u2019s, Hartford;"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1754","reference":[{"issue":"2","key":"b1","series-title":"Pediatrics","first-page":"298","article-title":"The incidence of positional plagiocephaly: a cohort study","volume":"132","author":"Mawji\n \nA","year":"2013","unstructured":"Mawji\n \nA\n\n, \n\nVollman\n \nAR\n\n, \n\nHatfield\n \nJ\n\n, \n\n\n. \nThe incidence of positional plagiocephaly: a cohort study\n. \nPediatrics\n. \n2013\n;\n132\n(\n2\n):\n298\n\u2013\n304\n."},{"issue":"5","key":"b2","series-title":"Plast Reconstr Surg","first-page":"1261","article-title":"Evidence-based medicine: craniosynostosis","volume":"133","author":"Fearon\n \nJA","year":"2014","unstructured":"Fearon\n \nJA\n\n\n. \nEvidence-based medicine: craniosynostosis\n. \nPlast Reconstr Surg\n. \n2014\n;\n133\n(\n5\n):\n1261\n\u2013\n1275\n."},{"issue":"3","key":"b3","series-title":"Transl Pediatr","first-page":"247","article-title":"Endoscopic craniosynostosis repair","volume":"3","author":"Proctor\n \nMR","year":"2014","unstructured":"Proctor\n \nMR\n\n\n. \nEndoscopic craniosynostosis repair\n. \nTransl Pediatr\n. \n2014\n;\n3\n(\n3\n):\n247\n\u2013\n258\n."},{"issue":"1","key":"b4","series-title":"J Craniofac Surg","first-page":"96","article-title":"Age at initial consultation for craniosynostosis: comparison across different patient characteristics","volume":"24","author":"Seruya\n \nM","year":"2013","unstructured":"Seruya\n \nM\n\n, \n\nOh\n \nAK\n\n, \n\nBoyajian\n \nMJ\n\n, \n\n\n. \nAge at initial consultation for craniosynostosis: comparison across different patient characteristics\n. \nJ Craniofac Surg\n. \n2013\n;\n24\n(\n1\n):\n96\n\u2013\n98\n."},{"key":"b5","series-title":"SIGGRAPH \u201904: ACM SIGGRAPH 2004 Papers","first-page":"309","article-title":"Grabcut \u2014 interactive foreground extraction using iterative graph cuts","author":"Rother\n \nC","year":"2004","unstructured":"Rother\n \nC\n\n, \n\nKolmogorov\n \nV\n\n, \n\nBlake\n \nA\n\n\n. \nGrabcut \u2014 interactive foreground extraction using iterative graph cuts\n. 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