Synthetic Skull Bone Defects for automatic Patient-specific Craniofacial Implant Design

Jianning Li, Christina Schwarz-Gsaxner, Antonio Pepe, Ana Morais, Victor Alves, Gord von Campe, Jürgen Wallner*, Jan Egger*

*Korrespondierende/r Autor/-in für diese Arbeit

Publikation: Beitrag in einer FachzeitschriftArtikelBegutachtung

Abstract

Patient-specific craniofacial implants are used to repair skull bone defects after trauma or surgery. Currently, cranial implants are designed and produced by third-party suppliers, which is usually time-consuming and expensive. Recent advances in additive manufacturing made the in-hospital or in-operation-room fabrication of personalized implants feasible. However, the implants are still manufactured by external companies. To facilitate an optimized workflow, fast and automatic implant manufacturing is highly desirable. Data-driven approaches, such as deep learning, show currently great potential towards automatic implant design. However, a considerable amount of data is needed to train such algorithms, which is, especially in the medical domain, often a bottleneck. Therefore, we present CT-imaging data of the craniofacial complex from 24 patients, in which we injected various artificial cranial defects, resulting in 240 data pairs and 240 corresponding implants. Based on this work, automatic implant design and manufacturing processes can be trained. Additionally, the data of this work build a solid base for researchers to work on automatic cranial implant designs.
Originalspracheenglisch
Aufsatznummer36
FachzeitschriftScientific Data
Jahrgang8
Ausgabenummer1
DOIs
PublikationsstatusVeröffentlicht - Dez 2021

ASJC Scopus subject areas

  • Information systems
  • Ausbildung bzw. Denomination
  • Bibliotheks- und Informationswissenschaften
  • Statistik und Wahrscheinlichkeit
  • Angewandte Informatik
  • Statistik, Wahrscheinlichkeit und Ungewissheit

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