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
Affiliations
Jianning Li
Corresponding authors.; Graz University of Technology (TU Graz), Graz, Styria, Austria; Computer Algorithms for Medicine Laboratory (Café Lab), Graz, Styria, Austria; Medical University of Graz (MedUni Graz), Graz, Styria, Austria
Marcell Krall
Medical University of Graz (MedUni Graz), Graz, Styria, Austria
Florian Trummer
Medical University of Graz (MedUni Graz), Graz, Styria, Austria
Afaque Rafique Memon
Institute of Biomedical Manufacturing and Life Quality Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
Antonio Pepe
Graz University of Technology (TU Graz), Graz, Styria, Austria; Computer Algorithms for Medicine Laboratory (Café Lab), Graz, Styria, Austria
Christina Gsaxner
Graz University of Technology (TU Graz), Graz, Styria, Austria; Computer Algorithms for Medicine Laboratory (Café Lab), Graz, Styria, Austria; Medical University of Graz (MedUni Graz), Graz, Styria, Austria
Yuan Jin
Graz University of Technology (TU Graz), Graz, Styria, Austria; Computer Algorithms for Medicine Laboratory (Café Lab), Graz, Styria, Austria; Research Center for Connected Healthcare Big Data, ZhejiangLab, Hangzhou, Zhejiang, China
Xiaojun Chen
Institute of Biomedical Manufacturing and Life Quality Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
Hannes Deutschmann
Medical University of Graz (MedUni Graz), Graz, Styria, Austria
Ulrike Zefferer
Medical University of Graz (MedUni Graz), Graz, Styria, Austria
Ute Schäfer
Medical University of Graz (MedUni Graz), Graz, Styria, Austria
Gord von Campe
Medical University of Graz (MedUni Graz), Graz, Styria, Austria
Jan Egger
Corresponding authors.; Graz University of Technology (TU Graz), Graz, Styria, Austria; Computer Algorithms for Medicine Laboratory (Café Lab), Graz, Styria, Austria; Medical University of Graz (MedUni Graz), Graz, Styria, Austria
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.
