Research Data Leeds Repository

Digital database of nose models for nasal prosthesis design generated with 3D morphable face model approach

Jablonski, Rachael Y and Bojke, Chris and Pavitt, Sue H and Nattress, Brian R and Keeling, Andrew J (2023) Digital database of nose models for nasal prosthesis design generated with 3D morphable face model approach. University of Leeds. [Dataset] https://doi.org/10.5518/1228

Dataset description

Designing nasal prostheses can be challenging due to the unpaired nature of the facial feature which precludes the use of mirroring techniques. It can be particularly difficult to accurately replace the missing tissue when preoperative information about the previous anatomy is unavailable or inadequate. In such situations, a database of nose models could act as a helpful starting point for the computer-aided design of a nasal prosthesis. Various digital nose model libraries are described in the literature based upon the facial scans of volunteers or anatomic casts. However, these libraries do not appear to be readily accessible to researchers or clinicians. Therefore, an open-access digital database of nose models has been generated based upon a 3D Morphable Face Model approach. This database comprises a manageable number of 44 simple, well-behaved nose meshes with standardized alignment that are ideal for computer-aided design.

Keywords:

Maxillofacial Prosthesis; Nasal Prosthesis; Computer-Aided Design; 3D Morphable Model

Subjects:

A000 - Medicine & dentistry

Divisions:

Faculty of Medicine and Health > School of Dentistry

License:

Creative Commons Attribution 4.0 International (CC BY 4.0)

Date deposited:

27 Mar 2023 12:02

URI:

http://archive.researchdata.leeds.ac.uk/id/eprint/1084

Additional details

Creators:

Creators	ORCID	Primary affiliation	Primary affiliation ID	Primary affiliation ID type
Jablonski, Rachael Y	https://orcid.org/0000-0001-5034-9831	University of Leeds	https://ror.org/024mrxd33	ror
Bojke, Chris	https://orcid.org/0000-0003-2601-0314	University of Leeds	https://ror.org/024mrxd33	ror
Pavitt, Sue H	https://orcid.org/0000-0001-7447-440X	University of Leeds	https://ror.org/024mrxd33	ror
Nattress, Brian R	https://orcid.org/0000-0001-9792-5154	University of Leeds	https://ror.org/024mrxd33	ror
Keeling, Andrew J	https://orcid.org/0000-0003-4598-3744	University of Leeds	https://ror.org/024mrxd33	ror

Type of data:

Dataset

Research funders:

NIHR, Leeds Hospitals Charity

Grant numbers:

NIHR300235, ULXXO.A200515

Publication date:

2023

Legal and ethical issues:

Rachael Jablonski, NIHR Doctoral Fellow, NIHR300235 is funded by the National Institute for Health and Care Research (NIHR) for this research project. The research is supported by the NIHR infrastructure at Leeds. The views expressed in the dataset and related publication are those of the authors and not necessarily those of the NIHR, NHS or the UK Department of Health and Social Care. The doctoral research is also supported by Leeds Hospitals Charity [Funding for Research and Innovation, Rachael Jablonski, ULXXO/A200515]. The funding sources had no influence in the conduct of the study, writing of the report, or the decision to submit the manuscript for publication.

Resource language:

English

Research project title:

IMPRESSeD: IMproving facial PRosthesis construction with contactlESs Scanning & Digital workflow, a feasibility cross-over randomised controlled trial of digital versus conventional manufacture for facial prostheses in patients post-surgery for head and neck cancer, IMPRESSeD: IMproving facial PRosthesis construction with contactlESs Scanning and Digital workflow.

Publisher:

University of Leeds

Contact Email Address:

r.jablonski@leeds.ac.uk

Last Modified:

27 Mar 2023 22:35