AI Article Synopsis

  • Patients with facial cancers often deal with significant changes in appearance, which can affect their self-image and how they are perceived by others.
  • A new method was developed to simulate realistic facial disfigurements using advanced imaging techniques and modeling, allowing for a better understanding of how people perceive these changes.
  • The approach demonstrated high accuracy and received positive evaluations from medical professionals, indicating it's a promising tool for future research on facial disfigurement and its social implications.

Article Abstract

Background: Patients with facial cancers can experience disfigurement as they may undergo considerable appearance changes from their illness and its treatment. Individuals with difficulties adjusting to facial cancer are concerned about how others perceive and evaluate their appearance. Therefore, it is important to understand how humans perceive disfigured faces. We describe a new strategy that allows simulation of surgically plausible facial disfigurement on a novel face for elucidating the human perception on facial disfigurement.

Method: Longitudinal 3D facial images of patients (N = 17) with facial disfigurement due to cancer treatment were replicated using a facial mannequin model, by applying Thin-Plate Spline (TPS) warping and linear interpolation on the facial mannequin model in polar coordinates. Principal Component Analysis (PCA) was used to capture longitudinal structural and textural variations found within each patient with facial disfigurement arising from the treatment. We treated such variations as disfigurement. Each disfigurement was smoothly stitched on a healthy face by seeking a Poisson solution to guided interpolation using the gradient of the learned disfigurement as the guidance field vector. The modeling technique was quantitatively evaluated. In addition, panel ratings of experienced medical professionals on the plausibility of simulation were used to evaluate the proposed disfigurement model.

Results: The algorithm reproduced the given face effectively using a facial mannequin model with less than 4.4 mm maximum error for the validation fiducial points that were not used for the processing. Panel ratings of experienced medical professionals on the plausibility of simulation showed that the disfigurement model (especially for peripheral disfigurement) yielded predictions comparable to the real disfigurements.

Conclusions: The modeling technique of this study is able to capture facial disfigurements and its simulation represents plausible outcomes of reconstructive surgery for facial cancers. Thus, our technique can be used to study human perception on facial disfigurement.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4396629PMC
http://dx.doi.org/10.1186/s12880-015-0050-7DOI Listing

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