MUG500+: Database of 500 high-resolution healthy human skulls and 29 craniotomy skulls and implants

Jianning Li*, Marcell Krall, Florian Trummer, Afaque Rafique Memon, Antonio Pepe, Christina Gsaxner, Yuan Jin, Xiaojun Chen, Hannes Deutschmann, Ulrike Zefferer, Ute Schäfer, Gord von Campe, Jan Egger*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In this article, we present a skull database containing 500 healthy skulls segmented from high-resolution head computed-tomography (CT) scans and 29 defective skulls segmented from craniotomy head CTs. Each healthy skull contains the complete anatomical structures of human skulls, including the cranial bones, facial bones and other subtle structures. For each craniotomy skull, a part of the cranial bone is missing, leaving a defect on the skull. The defects have various sizes, shapes and positions, depending on the specific pathological conditions of each patient. Along with each craniotomy skull, a cranial implant, which is designed manually by an expert and can fit with the defect, is provided. Considering the large volume of the healthy skull collection, the dataset can be used to study the geometry/shape variabilities of human skulls and create a robust statistical model of the shape of human skulls, which can be used for various tasks such as cranial implant design. The craniotomy collection can serve as an evaluation set for automatic cranial implant design algorithms.

Original languageEnglish
Article number107524
JournalData in Brief
Volume39
DOIs
Publication statusPublished - Dec 2021

Keywords

  • Computer-aided design (CAD)
  • Cranial implant design
  • Craniotomy
  • deep learning
  • Machine learning
  • Patient-specific implants (PSI)
  • Skull

ASJC Scopus subject areas

  • General

Cooperations

  • BioTechMed-Graz

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