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Anonymity of Medical Brain Images  

Lee, Hyo-Jong (Div. of Computer Science and Engineering, CAIIT, Chonbuk National University)
Du, Ruoyu (Div. of Computer Science and Engineering, Chonbuk National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.49, no.1, 2012 , pp. 81-87 More about this Journal
Abstract
The current defacing method for keeping an anonymity of brain images damages the integrity of a precise brain analysis due to over removal, although it maintains the patients' privacy. A novel method has been developed to create an anonymous face model while keeping the voxel values of an image exactly the same as that of the original one. The method contains two steps: construction of a mockup brain template from ten normalized brain images and a substitution of the mockup brain to the brain image. A level set segmentation algorithm is applied to segment a scalp-skull apart from the whole brain volume. The segmented mockup brain is coregistered and normalized to the subject brain image to create an anonymous face model. The validity of this modification is tested through comparing the intensity of voxels inside a brain area from the mockup brain with the original brain image. The result shows that the intensity of voxels inside from the mockup brain is same as ones from an original brain image, while its anonymity is guaranteed.
Keywords
MRI; level set; facial mask; skull extraction; anonymous facial model;
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