Machine Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Random Subspace Method for Constructing Decision Forests
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Earth Mover's Distance as a Metric for Image Retrieval
International Journal of Computer Vision
Shape versus Size: Improved Understanding of the Morphology of Brain Structures
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Performance Issues in Shape Classification
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part I
Combining Fisher Linear Discriminants for Dissimilarity Representations
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
The Dissimilarity Representation for Pattern Recognition: Foundations And Applications (Machine Perception and Artificial Intelligence)
Signatures versus histograms: Definitions, distances and algorithms
Pattern Recognition
Prototype selection for dissimilarity-based classifiers
Pattern Recognition
A concise and provably informative multi-scale signature based on heat diffusion
SGP '09 Proceedings of the Symposium on Geometry Processing
Volumetric heat kernel signatures
Proceedings of the ACM workshop on 3D object retrieval
Shape Recognition with Spectral Distances
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dissimilarity-based detection of schizophrenia
International Journal of Imaging Systems and Technology
A new shape diffusion descriptor for brain classification
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part II
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We apply shape analysis by means of heat diffusion and we show that dissimilarity space constructed using the features extracted from heat diffusion present a promising way of discriminating between schizophrenic patients and healthy controls. We use 30 patients and 30 healthy subjects and we show the effect of several dissimilarity measures on the classification accuracy of schizophrenia using features extracted by heat diffusion. As a novel approach, we propose an adaptation of random subspace method to select random subsets of bins from the original histograms; and by combining the dissimilarity matrices computed by this operation, we enrich the dissimilarity space and show that we can achieve higher accuracies.