Cluster-based classification using self-organising maps for medical image databases

摘要

Images are a fundamental source of information in modern 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.