Classification-Driven Pathological Neuroimage Retrieval Using Statistical Asymmetry Measures
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
A similarity measure based on causal neighbours and mutual information
Design and application of hybrid intelligent systems
Automatic detection of PET lesions
VIP '02 Selected papers from the 2002 Pan-Sydney workshop on Visualisation - Volume 22
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In this work, we report on a prototype of a clinical radiograph image database to be indexed by image content. The underlying content-based search engine is based on the modal shape description method for characterizing the shape of a \mbox{2-D} image region \cite{Scl95}. Using a similarity metric defined in a modal vector space, our system successfully classified radiographic images according to the dental pathologies they depicted. This successful classification demonstrates that the proposed similarity metric effectively captures clinical similarity between images in the database. The prototype is implemented in a Web-based environment, allowing remote users in the field to search a central repository of images. Examples of classification performance and typical queries are provided.