Constructing Subject- and Disease-Specific Effect Maps: Application to Neurodegenerative Diseases
File(s)
Accepted version
Author(s)
Konukoglu, E
Glocker, B
Type
Conference Paper
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.
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.
Date Issued
2016-10-17
Date Acceptance
2016-07-28
Citation
Lecture Notes in Computer Science
ISSN
0302-9743
Publisher
Springer
Journal / Book Title
Lecture Notes in Computer Science
Source
MICCAI Workshop on Medical Computer Vision: Algorithms for Big Data
Subjects
Artificial Intelligence & Image Processing
08 Information And Computing Sciences
Publication Status
Accepted
Start Date
2016-10-17
Finish Date
2016-10-21
Coverage Spatial
Athens, Greece