Anonymization of Facial Features in MRI Volumes
Thesis by: Christoph Niedermayr
Supervision by: Christian Lederer (TRIUM), AndreasKeil
The goal of this thesis is to detect and modify facial features in
volume MRI scans, allowing hospitals to publish diagnostic imagery
without compromising their patients' privacy. The problem can be
splitted into three major challenges:
- classify image as head or non-head
- detect facial features
- modify image data where necessary
In order to detect facial features, a given image will be registered
against a reference image containing a head. Registration will be done
in three phases, increasing the degrees of freedom as the registration
improves. In the reference image, crucial areas (e.g. eyes, jaw, nose)
are marked and can be mapped to the test image after registration.
Image classification will be done using a statistic model, based on
image properties and registration outcome.
In the end, the image data can be manipulated by e.g. deforming the
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