The research of facial palsy, a unilateral palsy of the facial nerve, is a complex field of study with many different causes and symptoms. Even modern approaches to evaluate the facial palsy state rely mainly on stills and 2D videos of the face and rarely on 3D information. Many of these analysis and visualization methods require manual intervention, which is time-consuming and error-prone. Moreover, existing approaches depend on alignment algorithms or Euclidean measurements and consider only static facial expressions. Volumetric changes by muscle movement are essential for facial palsy analysis but require manual extraction. Our proposed method extracts an estimated unilateral volumetric description for dynamic expressions from 3D scans. Accurate positioning of 3D landmarks, problematic for facial palsy, is automated by adapting existing methods. Additionally, we visualize the primary areas of volumetric disparity by projecting them onto the face. Our approach substantially minimizes human intervention simplifying the clinical routine and interaction with 3D scans. The proposed pipeline can potentially more effectively analyze and monitor patient treatment progress.
CITATION STYLE
Büchner, T., Sickert, S., Volk, G. F., Guntinas-Lichius, O., & Denzler, J. (2023). From Faces to Volumes - Measuring Volumetric Asymmetry in 3D Facial Palsy Scans. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 14361, pp. 121–132). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-47969-4_10
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