Abstract
Images are a fundamental source of information in medicine. They can support doctors and students in diagnostic decisions besides providing research and didactic material. The images stored in a database and divided in categories are an important step for data mining and content-based image retrieval (CBIR). This work addresses a methodology which joins the use of discrete wavelet transforms to characterise images and self-organising maps (SOM) neural networks to cluster based classification of medical images. This data mining methodology can be used in categorisation and in computer-aided diagnostic decision.
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