3D fetal face reconstruction from ultrasound imaging
| Autor: | Marius George Linguraru, Fatima Crispi, Araceli Morales, Antònia Alomar, Federico M. Sukno, Kilian Vellvé, Gemma Piella, Antonio R. Porras |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Computer science
Facial dysmorphology Prenatal diagnosis 0102 computer and information sciences 02 engineering and technology Fetal reconstruction 01 natural sciences Computer graphics 010201 computation theory & mathematics Computer graphics (images) 0202 electrical engineering electronic engineering information engineering Ultrasound imaging 020201 artificial intelligence & image processing Fetal face 3D morphable model Craniofacial morphology |
| Zdroj: | VISIGRAPP (4: VISAPP) |
| Popis: | Comunicació presentada al VISIGRAPP 2021: The 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, celebrat del 8 al 10 de febrer de 2021 de manera virtual. The fetal face contains essential information in the evaluation of congenital malformations and the fetal brain function, as its development is driven by genetic factors at early stages of embryogenesis. Three-dimensional ultrasound (3DUS) can provide information about the facial morphology of the fetus, but its use for prenatal diagnosis is challenging due to imaging noise, fetal movements, limited field-of-view, low soft-tissue contrast, and occlusions. In this paper, we propose a fetal face reconstruction algorithm from 3DUS images based on a novel statistical morphable model of newborn faces, the BabyFM. We test the feasibility of using newborn statistics to accurately reconstruct fetal faces by fitting the regularized morphable model to the noisy 3DUS images. The algorithm is capable of reconstructing the whole facial morphology of babies from one or several ultrasound scans to handle adverse conditions (e.g. missing parts, noisy data), and it has the potential to aid in-utero di agnosis for conditions that involve facial dysmorphology. This work is partly supported by the Spanish Ministry of Economy and Competitiveness under project grant TIN2017-90124-P, and the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502). |
| Databáze: | OpenAIRE |
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