Abstract
Biomedical informatics refers to the study of the application of computational
and statistical algorithms, data structures, and methods to improve communication, understanding and management of biomedical information. Our objective through this chapter is to describe and demonstrate our research in the use of biomedical image databases - in both preclinical and clinical settings - to classify, predict, research, diagnose, and otherwise learn from the informational content encapsulated in historical image repositories. This will be accomplished by detailing our approach of describing image content in a Bayesian probabilistic framework to achieve learning from retrieved populations of similar images. We will use specific examples from two biomedical applications to describe anatomic segmentation, statistical feature
generation and indexing, efficient retrieval architectures, and predictive results.
