HuCS-ID Lab: Data resources
The HuCS-ID lab has developed several specialised data resources that that students can leverage for their research studies/degrees in craniofacial or skeletal identification. These resources additionally facilitate advanced subject matter workshops to industry / government, per consultancies arranged through UQ’s Consulting and Research Expertise unit, CoRE.
The resources include two sets of ultra-resolution medical images (MR and CT) for studying craniofacial anatomy and a specialized library of skeletons with matching pre-skeletisation radiographs (as pertinent to identification).
AP Stephan also curates the Collaborative Facial Soft Tissue Depth Data Store (at CRANIOFACIALidentification.com), which is an open-access, free, and online data resource for all craniofacial identification practitioners to use.
Further details on these resources can be found below.
HuCS-ID CT & MR Head Dataset (Decedents)
This resource comprises both CT and MR scans of 91body donors to UQ’s anatomy program, acquired between 2023-24. These scans are taken with UQ ethics office approvals and full donor consents. Each subject in this database is represented by five scans: one axial CT, one sagittal CT, and three sets of 3T MRIs (T1-weighted MRI, T2-weighted MRI and PETRA ultrashort echo time). This dataset holds the advantage that the decedents are precisely still during the scans, yielding very high image qualities when combined with the ultra-high resolution slice thicknesses (CT = 0.75 mm slice thickness with 0.5mm slice overlap; MRI = 0.65 mm slice thickness in most cases). The scans are full-length of the head. Equivalent whole-head CT scans for living individuals are not possible under these high-resolution parameters because of the imaging intensity required providing a unique dataset.
All scans are acquired at UQ’s Centre for Advanced Imaging (CAI) using their latest Siemens equipment/software (Biograph Horizon CT scanner and Magnetrom Prisma 3T).
CT and MR machines used for data collection at the CAI.
HuCS-ID MR Head Dataset (Living Persons)
This resource represents 3T MRI scans (4 for each living subject), with the first scans being acquired in 2025. By the end of the data collection period, we anticipate to hold scans for 200 living subjects. These scans include T1-weighted MRI, T2-weighted MRI and PETRA ultrashort echo time for each subject. The scan resolutions are ultra-high using ≤0.65 mm slice thickness.
All scans are acquired at UQ’s Centre for Advanced Imaging (CAI) using their latest Siemens Magnetrom Prisma 3T whole body MR and are being taken in conjunction with Telena Hona’s PhD research project (see Team tab for more information).
SBMS Skeletal Collection
This data resource comprises radiographs and skeletons belonging to a subset of Type II (indefinite) body donors to the UQ Body Donor and Anatomy program.
The dry skeletons are 100% traceable to single individuals of origin, and each is accompanied by 8-10 standard radiographs taken prior to skeletisation and all are ethically resourced through the UQ Body Donor Program. These three attributes set this collection apart from other skeletal collections available in the global domain.
Image reproduced from: Stephan, C. N., Caple, J. M., Veprek, A., Sievwright, E., Kippers, V., Moss, S., & Fisk, W. (2017). Complexities and Remedies of Unknown-provenance Osteology. In N. Pather & G. Strkalj (Eds.), Commemorations and Memorials in Anatomy: Tribute to the Giver (pp. 65-95).
The Collaborative Facial Soft Tissue Depth Data Store (C-Table)
The C-table represents a publicly available and centralised online repository of anonymized raw facial soft tissue depth data for the field of craniofacial identification. It is free to access and separately maintained and updated on a continuing basis by Associate Professor Stephan. Currently, the repository holds data contributed by 20 different research teams (see the C-Table website for details), representing >1,700 individuals collected at up to 25 standardized craniofacial landmarks.
The C-Table is available at CRANIOFACIALidentification.com.
