Factor Analysis and the Retrieval of Medical Images Depicting Structures with Similar Shapes

This work presents a new perspective to medical image retrieval based on factor analysis. The shape of anatomical structures are represented as high-dimensional sets of vector variables obtained from non-rigidly deforming a template image so as to align its anatomy with the subject anatomy of a group. By eliminating the redundancy embedded in the data, a reduced set of factors is determined, corresponding to new variables with possible anatomic significance. The method’s ability to retrieve relevant images is exemplified in a study of the corpus callosum, a structure with very subtle shape differences. The factor analysis approach is compared to principal component analysis in a set of 960 experiments, yielding significantly higher precision rates.

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