Abstract
Current statistical methods in neuroimaging identify effects of neurodegenerative diseases on the brain structure by detecting group differences. Results are detailed maps showing population-wide effects. Although useful for better understanding the disease, these maps provide little subject-specific information. Furthermore, since group assignments have to be known prior to analysis, resulting maps have limited diagnostic value for new subjects. This article proposes a method to construct subject- and disease-specific effect maps prior to diagnosis. The method combines techniques from binary classification and image restoration to identify the effects of a disease of interest on the measurements. Experimental evaluation is carried out with synthetically generated data and real data selected from the ADNI cohort. Results demonstrate the capability of the proposed method in generating subject-specific effect maps.
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Konukoglu, E., Glocker, B. (2017). Constructing Subject- and Disease-Specific Effect Maps: Application to Neurodegenerative Diseases. In: Müller, H., et al. Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging. BAMBI MCV 2016 2016. Lecture Notes in Computer Science(), vol 10081. Springer, Cham. https://doi.org/10.1007/978-3-319-61188-4_1
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DOI: https://doi.org/10.1007/978-3-319-61188-4_1
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