The biological evidence that links facial and brain development gives rise to the
long-standing hypothesis on the relation between facial geometry and some
neuropsychiatric disorders. However, the existence of studies directly comparing face
and brain data is still scarce. Thus, this study was part of a research project that aimed to
detect whether morphological brain abnormalities linked to schizophrenia may also be
related to abnormalities in the face geometry. A novel database of Magnetic ...
The biological evidence that links facial and brain development gives rise to the
long-standing hypothesis on the relation between facial geometry and some
neuropsychiatric disorders. However, the existence of studies directly comparing face
and brain data is still scarce. Thus, this study was part of a research project that aimed to
detect whether morphological brain abnormalities linked to schizophrenia may also be
related to abnormalities in the face geometry. A novel database of Magnetic Resonance
scans of the head of schizophrenia and control patients was used to explore the
existence of this link.
The role of this study in the project was to develop the pipeline to extract meaningful
facial characteristics. Twenty head scans were processed, ten of which were considered
outliers due to their high levels of noise. Consequently, the project focused on
eliminating the noise present in the volumes without losing geometry details. The
pipeline is formed by an initial pre-processing block to eliminate part of the mentioned
noise, followed by facial region segmentation through several pixel intensity-based
methods. Finally, as noise remained in some cases, two public 3D Morphable Head
Models were employed to deform a template head mesh extracted from these models to
the target heads obtained in the segmentation, followed by a mesh refinement of the
deformed head. In this way, all the subjects were brought into correspondence, having
the same number of vertices and triangles for further statistical analysis.
This study presents the different methods applied in the pre-processing and
segmentation steps, the parameters tested in the two statistical methods, and the
methods tested in the mesh refinement, all with their corresponding results. Finally, it
outlines the ones that gave results with enough quality for the extraction of facial
features. Thereby, this approach could be employed as an initial step in the research
project's goal to detect the possible facial dysmorphogenesis linked to brain
abnormalities and schizophrenia.
+