Scalable digital solutions for reconstructive surgery. Rapid prediction of 3D face and body morphology in low-resource conditions
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DOI der Originalpublikation
Zugehörige Forschungsdaten
Projekttyp
angewandte Forschung
Projektbeginn
18.08.2025
Projektende
17.08.2026
Projektstatus
laufend
Projektkontakt
Projektmanager:in
Mitarbeitende
Beschreibung
Zusammenfassung
This project advances AI-driven 3D and AR content creation for reconstructive and aesthetic surgery by developing a mobile-first, privacy-preserving platform for the automated generation of high-quality 3D face and body models from 2D images. Today's tools depend on special scanners, full video capture, or cloud processing, making them costly, hard to access, and a concern for patient privacy. We address these limits using generative AI, Gaussian splatting, and neural rendering to reconstruct reliable 3D models from just a handful of images. The work combines research on sparse-view reconstruction with methods for generating pseudo-ground-truth models and building real-world capture datasets. We also study how to run these models directly on smartphones and tablets, so 3D modeling works in real time without sending data to the cloud and patient privacy is protected by design. The goal is a scalable and affordable solution that lowers the barrier for clinics.
Link
Während FHNW Zugehörigkeit erstellt
Ja
Zukunftsfelder FHNW
Future Health
Hochschule
Hochschule für Informatik FHNW
Institut
Institut für Interaktive Technologien
Finanziert durch
Innosuisse
Projektpartner
Arbrea Labs AG
Auftraggeberschaft
SAP Referenz
Schlagwörter
Generative AI
Extended reality
3D models
Extended reality
3D models