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1 Ergebnisse
1
CNN-Based Classification of Craniosynostosis Using 2D Dista..:
, In:
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
,
Schaufelberger, Matthias
;
Ktihle, Reinald Peter
;
Kaiser, Christian
... - p. 446-449 , 2022
Link:
https://doi.org/10.1109/EMBC48229.2022.9871526
RT T1
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
: T1
CNN-Based Classification of Craniosynostosis Using 2D Distance Maps
UL https://suche.suub.uni-bremen.de/peid=ieee-9871526&Exemplar=1&LAN=DE A1 Schaufelberger, Matthias A1 Ktihle, Reinald Peter A1 Kaiser, Christian A1 Wachter, Andreas A1 Weichel, Frederic A1 Hagen, Niclas A1 Ringwald, Friedemann A1 Eisenmann, Urs A1 Freudlsperger, Christian A1 Nahml, Werner YR 2022 SN 2694-0604 K1 Pathology K1 Pediatrics K1 Head K1 Three-dimensional displays K1 Shape K1 Computed tomography K1 Imaging K1 Clinical relevance- The gold standard for the diagnosis of craniosynostosis is computed tomography imaging. Yet K1 this exposes infants to ionizing radiation which should be avoided due to an increased risk of developing intracranial neoplasms or leukemia. This contribution proposes a mapping method to obtain 2D images from 3D head surface scans K1 enabling a radiation-free K1 CNN-based diagnosis of craniosynostosis SP 446 OP 449 LK http://dx.doi.org/https://doi.org/10.1109/EMBC48229.2022.9871526 DO https://doi.org/10.1109/EMBC48229.2022.9871526 SF ELIB - SuUB Bremen
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