Cliniface is a desktop software application for Windows and Linux that provides visualisation, analysis, and reporting tools for 3D facial images. The application is aimed primarily at medical professionals who seek to leverage 3D facial images to explore the richness of the facial surface to visualise, identify, and communicate cues of syndromic or surgical relevance. Cliniface enables collaborative consultation by bringing the ‘digital patient’ into the room – reducing the occurrence and duration of patient visits with a clinician, and augmenting and enhancing a clinician’s abilities in making timely and accurate facial assessments.

The software was initially developed in a research environment as an easy-to-use desktop tool to quickly clean and standardise raw 3D facial images captured in a variety of formats in preparation for further analysis. The flexibility in its design means that new state-of-the-art methods in 3D facial processing, visualisation, and analysis can be easily integrated.

Cliniface uses a plugin architecture to allow functionality developed by third-parties to be incorporated. This provides researchers and programmers working with 3D facial images the means to rapidly develop, test, and deploy in a practical setting new algorithms without needing to develop extraneous visualisation and file I/O routines. This mechanism offers researchers a simplified pathway for their algorithms to enter mainstream use – helping to bridge the gap between scientific and research outputs, and the employment of those state-of-the-art algorithms in clinical practice.

Cliniface and its software libraries are completely free and open-source, and is made available under the GNU General Public License v3.

Features

Cliniface is being continuously improved; we like to build relationships with our users so we can determine the features to develop for upcoming versions of the software that will have the most benefit. The following is an (incomplete) list of features in the most recent version:

State-of-the-art detection of 40 standard anatomical facial landmarks with automatic alignment

Measurements of more than 50 different facial features

Five different metric types (distance, angle, depth, asymmetry, region)

Automatic identification of more than 45 different facial HPO terms

Uses transparent and objective criteria for identifying HPO terms

Uses existing anthropometric statistics from the research literature

Surface visualisations including asymmetry and curvature

User defined ad hoc facial measurements using “virtual callipers”

Side-by-side comparison of measurements from different images

Built-in geometry cleaning and rectification tools

Interoperability and communication of analysis; links to the online HPO database, XML/JSON analysis export, and report generation

Export fully viewable 3D models within PDF documents

Association of demographic and clinical assessment notes and incorporation of multiple assessments

Comprehensive and context aware help documentation

Intuitive and easy to use interface

Free and Open Source Software (FOSS)

Installs without administrator privileges

Can be run directly from a USB memory stick

Screenshots